As a natural ecological fragile region, the vast desert steppe in the Inner Mongolia has a developed animal husbandry, and thus posed great impacts on soil quality. In order to accurately evaluate the current situation of soil quality in the desert steppe, it is therefore imperative to adopt a suitable method to effectively assess the soil quality in the region. In this study, the minimum data set (MDS) was established with the help of principal component analysis, Norm value calculation, and correlation analysis, and four indicators, including organic matter, sand grains, soil erosion degree, and pH, were established to evaluate the soil quality of the desert steppe in the Siziwang Banner, a county in the Inner Mongolia. The results from the minimum data set (MDS) method were validated based on the total data set (TDS) method, and the validation indicated that the MDS method can be representative of the soil quality of the study area. The results indicated: 1) the soil quality index (SQI) of 0-30 cm in more than 90% of the study area falls in the range of 0.4 and 0.6 (medium level), while the better level (SQI ≥0.6) only accounted less than 10% of the study area; 2) For the MDS indexes, soil organic matter content at all depths decreased in the southern mountains, central hills, and northern plateau, which is consistent with the changing trends of SQI; 3) The sand grain was the dominant particle in the study region, which was in accordance with the intense wind erosion; 4) The negative correlation was found between the soil pH value and SQI (the high value in pH corresponded to the low value in SQI), which reflected that soil pH has a more stressful effect on the local vegetation. Overall, the MDS indexes in this study can objectively and practically reflect the soil quality in the study area, which can provide a cost effective method for SQI assessment in the desert steppe, which is important for the further grassland ecological construction and grassland management to improve the soil quality in the desert steppes.
Copyright: © 2023 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.