Soil quality assessment of karst trough valley under different bedrock strata dip and land-use types, based on a minimum data set

Abstract

Typical bedrock strata dips and land use types can significantly influence the soil quality in karst trough valleys. However, data on the influence of bedrock strata dips on the assessment of soil quality based on the soil quality index in karst trough valleys are limited. Thus, the aim of this study was to investigate the impact of different land use types and bedrock strata dips on soil quality and to evaluate the suitability of soil quality assessment methods for karst trough valleys. Five land-use types were selected as research objects for each dip and anti-dip slope, and a total data set (TDS) consisting of soil physico-chemical properties and soil microbial property indices was collected. The minimum data set (MDS) was constructed using principal component analysis (PCA) and norm values, and two evaluation methods, i.e., linear (SQI-L) and non-linear (SQI-NL) were used to assess the soil quality in the study area. The results showed that the order of weight of the MDS was urease activity > protease activity > silt > soil bulk density > total phosphorus. The overall soil quality obtained from the SQI-L and SQI-NL models exhibited similar results for the dip slope; however, there were differences in the details of the anti-dip slope. The soil quality of the anti-dip slope was better than that of the dip slope (P < 0.05) and the soil quality indices of the forest and grassland were significantly higher than those of the other land use types (P < 0.05). Furthermore, the SQI-NL model can accurately replace the SQI-L model for soil quality evaluation based on its high variation interval and variable coefficients. Overall, our results suggest that the SQI-NL model is suitable for soil quality evaluation on dip and anti-dip slopes, and returning farmland to forest is an effective land-use change in the karst trough valleys.