Mechanisms of land use change effects on soil quality in ancient terraces based on the minimum data set approach

• Published in: Catena (Giessen) Vol. 254; p. 108990
• Main Authors: Peiyao, Xiao, Yuying, Hao, Yaojun, Liu, Chuxiong, Deng, Wenqing, Li, Guangye, Zhang, Taoxi, Li, Yichun, Ma, Ming, Lei, Yu, Long, Zhongwu, Li
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 30.06.2025
• Subjects: agroforestry; Ancient terraces; catenas; China; data collection; dissolved organic carbon; forests; Land use change; mountains; paddies; path analysis; regression analysis; rice; Scoring method; soil profiles; soil quality; Soil quality index; China; Soil quality index; Scoring method; Land use change; Ancient terraces
• ISSN: 0341-8162
• DOI: 10.1016/j.catena.2025.108990

[Display omitted] •This study investigates the impact of land use change on soil quality in terraces.•Land use changes in ancient rice terraces degrade soil quality by 43.9% and 47.3%.•DOC drives bacterial diversity changes, thereby impacting soil quality.•The MDS-SNL method reliably assessed soil quality changes in terraces. Widespread land use changes in ancient rice terraces significantly influence soil quality in mountainous regions, impacting its ecological functions. However, the effects of land use changes on soil quality and the underlying factors remain unclear. This study investigates ancient rice terraces and their conversion into dry lands and forest lands in Ziquejie, Hunan Province. Soil samples were collected from a 0–120 cm depth profile, and 14 physicochemical and 6 biological properties were assessed. Soil quality was assessed using linear and non-linear scoring techniques and three indicator selection methods (total, minimum, and revised minimum data sets). The findings showed that the non-linear scoring method was more reliable than the linear method for soil quality assessments. The minimum data set (MDS) from the non-linear scoring method demonstrated a significant coefficient of variation (CV) of 0.51, an F-value of 26.24, and a sensitivity index (SI) of 13.43, indicating its strong suitability for assessing soil quality. The transition from paddy fields to dry lands and forest lands resulted in a 43.9 % and 47.3 % decrease in soil quality, respectively. This land use change also caused a progressive decline in soil quality with depth, increasing reductions by 190.1 % and 131.8 %, respectively. Path analysis revealed that chemical properties significantly influence biological attributes, and multiple regression analysis further demonstrated that land use changes predominantly affect soil profile quality by regulating dissolved organic carbon (DOC), subsequently influencing bacterial diversity. The MDS non-linear assessment method effectively evaluates soil quality changes in terraces due to land use, primarily driven by biological and chemical factors. Future efforts should focus on minimizing terrace land use conversion to maintain soil quality and enhance productivity in agroforestry systems.