Several methods have been used to model reality and explain soil pedogenesis and evolution. However, there is a lack of information about which soil properties truly condition soil quality indicators and indices particularly at the pedon scale and at different soil depths to be used in land management planning. Thus, the main goals of this research were: i) to assess differences in soil properties (particle size, saturation point, bulk density, soil organic carbon, pH and electrical conductivity) at different soil depths (0-30 and 30-60 cm); ii) to check their statistical correlation with soil quality indicators (CEC, total N, Olsen-P, available K, exchangeable Na, calcium carbonate equivalent, Fe, Mn, Zn, and Cu); and, iii) to elaborate a soil quality index and maps for each soil layer. To achieve this, forty-eight soil samples were analysed in the laboratory and subjected to statistical analyses by ANOVA, Spearman Rank coefficients and Principal Component Analyses. Finally, a soil quality index was developed based on indicators of sensitivity. The study was conducted in a semiarid catchment in northeast Iran with irrigated farming and well-documented land degradation issues. We found that: i) organic carbon and bulk density were not similar in the topsoil and subsoil; ii) calcium carbonate and sand content conditioned organic carbon content and bulk density; iii) organic carbon showed the highest correlations with soil quality indicators; iv) particle size conditioned cation-exchange capacity; and, v) heavy metals such as Mn and Cu were highly correlated with organic carbon due to non-suitable agricultural practices. Based on the communality analysis to map of soil quality, CEC, Mn, Zn, and Cu had the highest weights (≥0.11) at both depths, coinciding with the same level of relevance in the multivariate analysis. Exchangeable Na, CaCO3, and Fe had the lowest weights (≤0.1) and N, P, and K had intermediate weights (0.1- 0.11). In general, the map of the soil quality index shows a lower soil quality in the subsoil increment than in the topsoil.
The use of multivariate statistical analysis and soil quality indices as tools to be included in regional management plans. A case study from the Mashhad Plain, Iran
