Establishing a soil quality index to evaluate soil quality after afforestation in a karst region of Southwest China

环境科学 土壤质量 土壤碳 加权 植树造林 索引(排版) 果园 土壤科学 土壤水分 数学 统计 水文学(农业) 农林复合经营 农学 地质学 计算机科学 放射科 万维网 生物 医学 岩土工程
作者
Pujia Yu,Jinlian Liu,Hanya Tang,Xizao Sun,Shiwei Liu,Xuguang Tang,Zhi Ding,Mingguo Ma,En Ci
出处
期刊:Catena [Elsevier BV]
卷期号:230: 107237-107237 被引量:37
标识
DOI:10.1016/j.catena.2023.107237
摘要

The improvement of soil quality (SQ) evaluation tools can contribute to more precise and efficient monitoring of SQ changes under different management practices. This study aimed to establish an effective and accurate soil quality index (SQI) using different indicator selecting methods (MDS, minimum data set; RMDS, revised minimum data set) and different weighted additive approaches (variance and communality weighted) to assess the effect of the conversion of farmland (FL) to three land use types (BA, bamboo forest; LAT, landscape tree planting; ORO, orange orchard) converted from similar farmland on SQ in a karst region of Southwest China. Six physical indicators, nine chemical indicators and seven biological indicators were measured at the 0–20 cm depth as potential SQ indicators. Four chemical indicators, including the very labile carbon fraction (LCF), macroaggregate-associated organic carbon, total potassium (TK) and available phosphorus, were identified as the MDS using principal component analysis. However, one physical indicator (sand), two chemical indicators (LCF and TK) and one biological indicator (bacterial Shannon diversity index) were retained in the RMDS. The average sensitivity index value of the SQIs calculated using the RMDS was 39.54% higher than that of the SQIs determined using the MDS. The range (max.-min.) of weighting values calculated by variance (0.55 and 0.10 for the MDS and RMDS, respectively) among the chosen soil indicators was greater than that calculated by communality (0.07 and 0.02 for the MDS and RMDS, respectively). The high sensitivity index value and great range of weighting values indicated that the SQI calculated by the RMDS and variance weighted exhibited better performance and discrimination in the evaluation of SQ than other SQIs. The SQI value under BA was the highest, followed by that under ORO and FL, and LAT had the lowest SQI value. In conclusion, land use changes significantly alter the SQ in Southwest China, and the SQI developed using the RMDS approach and the variance weighted method is recommended as a sensitive and effective tool for SQ evaluation under different land uses in Southwest China and other regions.
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