A global meta‐analysis of indicators for assessing forest soil quality through comparison between paired plantations versus natural forests

Abstract

AbstractSoil quality is defined as the capacity of soil to sustain biological productivity and healthy environments. More than 30 physical, chemical, and microbial properties have been used to assess soil quality status. However, using specific properties to represent forest soil quality remains ambiguous. Here, we conducted a meta‐analysis of paired natural and plantation forests using 104 articles and 26 soil indices to evaluate soil quality indicators. Principal component analysis (PCA) and correlation analysis were used to choose a minimum dataset (MDS) of soil quality indicators. Significant differences in 16 indices of soil properties, including 1 physical, 5 chemical and 10 microbial properties, were found between soils in natural versus plantation forests. The PCA and correlation analysis indicated that 7 indices, including total carbon (C) and nitrogen (N), microbial biomass C (MBC) and N (MBN), fungal biomass, bacterial biomass, and hydrolytic enzymes, can be used to establish an MDS that explains 76.8% of the data variation. Based on the MDS, total C and N, MBC, MBN, fungal biomass, bacterial biomass and hydrolytic enzymes contribute 17.9%, 14.9%, 22.2%, 16.7%, 15.2%, 8.3%, and 4.8% to the soil quality, respectively. The climate, stand age and tree species affect the intensity of variation in these 7 soil indicators, not the variation direction of these soil indicators. Our study indicates that soil C and N values and microbial properties are important forest soil quality indicators and that the intensity of variation in these soil indicators depends on the climate, stand age and tree species planted.