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Rocky desertification is a devastating process in Karst areas of Southwest China and induces serious fragmentation in ecosystems. Therefore, vegetation restoration and the scientific evaluation of soil quality are key restorative strategies in these areas. In this study, a natural closed forest and a disturbed forest with three restoration models, including an evergreen broad-leaved forest, mixed forest, and deciduous forest, were investigated in Huanjiang County. More than nineteen soil properties (including physical, chemical, and biotic properties) were analyzed across treatments, and principal component analyses (PCA) were combined with a minimum data set (MDS) applied to evaluate the soil quality. Our study sought to identify a vegetation restoration model to improve the soil quality in this area. We demonstrated that soil physical and chemical properties, microbial biomass, and enzyme activities significantly differed across all of the models. Soil water content, capillary porosity, total porosity, organic carbon, total phosphorus, available phosphorus, and urease activity were high in the mixed forest, leading to better physical soil properties. Also, relatively high soil total nitrogen, total potassium, available nitrogen, available potassium, microbial biomass C and N, catalase, sucrose, and alkaline phosphatase levels were observed in the deciduous broad-leaved forest, resulting in improved soil chemical properties. Based on the minimum data set (MDS) method, six indicators, including non-capillary porosity, organic carbon, total phosphorus, pH, microbial biomass nitrogen, and urease activity, were selected to evaluate the soil quality across the models. Our data showed that, among the five models, the deciduous broad-leaved forest had the highest soil quality index (0.618), followed by the mixed forest (0.593). Stepwise regression analysis showed that soil organic carbon explained 79.9% of the variations in the soil quality indices, suggesting it was a major factor affecting the soil quality. Thus, vegetation restoration models mainly comprised of native tree species effectively improved the soil quality in Karst rocky desertification areas, with deciduous broad-leaved forests displaying the best effects, followed by mixed forests.

Rocky desertification is a devastating process in Karst areas of Southwest China and induces serious fragmentation in ecosystems. Therefore, vegetation restoration and the scientific evaluation of soil quality are key restorative strategies in these areas. In this study, a natural closed forest and a disturbed forest with three restoration models, including an evergreen broad-leaved forest, mixed forest, and deciduous forest, were investigated in Huanjiang County. More than nineteen soil properties (including physical, chemical, and biotic properties) were analyzed across treatments, and principal component analyses (PCA) were combined with a minimum data set (MDS) applied to evaluate the soil quality. Our study sought to identify a vegetation restoration model to improve the soil quality in this area. We demonstrated that soil physical and chemical properties, microbial biomass, and enzyme activities significantly differed across all of the models. Soil water content, capillary porosity, total porosity, organic carbon, total phosphorus, available phosphorus, and urease activity were high in the mixed forest, leading to better physical soil properties. Also, relatively high soil total nitrogen, total potassium, available nitrogen, available potassium, microbial biomass C and N, catalase, sucrose, and alkaline phosphatase levels were observed in the deciduous broad-leaved forest, resulting in improved soil chemical properties. Based on the minimum data set (MDS) method, six indicators, including non-capillary porosity, organic carbon, total phosphorus, pH, microbial biomass nitrogen, and urease activity, were selected to evaluate the soil quality across the models. Our data showed that, among the five models, the deciduous broad-leaved forest had the highest soil quality index (0.618), followed by the mixed forest (0.593). Stepwise regression analysis showed that soil organic carbon explained 79.9% of the variations in the soil quality indices, suggesting it was a major factor affecting the soil quality. Thus, vegetation restoration models mainly comprised of native tree species effectively improved the soil quality in Karst rocky desertification areas, with deciduous broad-leaved forests displaying the best effects, followed by mixed forests. [ABSTRACT FROM AUTHOR]