Establishing a soil quality index to assess the effect of thinning on soil quality in a Chinese fir plantation

• Published in: European journal of forest research Vol. 141; no. 6; pp. 999 - 1009
• Main Authors: Ye, Yuqian, Sun, Xiaodan, Zhao, Jiahao, Wang, Meiquan, Guan, Qingwei
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2022; Springer Nature B.V
• Subjects: Biological properties; Biomass; Biomedical and Life Sciences; Carbon; Cunninghamia lanceolata; Datasets; Forest management; Forest practices; Forestry; Life Sciences; Mathematical analysis; Methods; Microorganisms; Organic carbon; Organic soils; Original Paper; Plant Ecology; Plant Sciences; Plantations; Precipitation; Principal components analysis; Quality assessment; Seasonal variations; Soil chemistry; Soil properties; Soil quality; Soils; Sustainability management; Sustainable forestry; Thinning; Thinning; Soil quality indicator; Soil quality index; Assessment method
• ISSN: 1612-4669; 1612-4677
• DOI: 10.1007/s10342-022-01471-7

Better knowledge and comprehensive evaluation of soil quality have important implications for developing sustainable forest management practices. The objective of the present study was to establish a soil quality index (SQI) that can be used to assess soil quality under different thinning intensities in a Chinese fir ( Cunninghamia lanceolata [Lamb.] Hook) plantation in southeastern China. We sampled the soil in different seasons of the year from four plots subjected to different thinning intensities: low-intensity thinning (LIT, 30%), moderate-intensity thinning (MIT, 50%), high-intensity thinning (HIT, 70%), and control (0%). We analyzed 16 physical, chemical, and biological soil properties. The SQI was calculated based on total data set (TDS) and minimum data set (MDS) using different scoring functions (linear and nonlinear), integrating procedures (additive, weighted additive, and Nemoro), and weight assignment methods (communality and variation of principal component analysis (PCA)). The SQI calculated by the nonlinear weighted additive method with variation explained by the PCA performed better than the other methods. The SQI values were in the range of 0.26–0.64 under different thinning intensities. A significant increase in the SQI values was observed in MIT (53.2%) and HIT (40.8%) compared with that in CK. The SQI values also showed strong seasonal variability, with the highest values in the summer and the lowest values in the winter. Microbial biomass nitrogen (MBN), soil organic carbon (SOC), and pH were found to be the most crucial indicators of soil quality. Our results confirmed that thinning exerts a strong effect on soil quality, and the studied SQI based on MDS was found to be an effective tool for assessing soil quality.