Conversion of farmland to forest or grassland improved soil C, N and multi-functionality in a subtropical karst region, southwest China

Lijin Zhang,Hu Du,Tongqing Song, Zhiqi Yang,Wanxia Peng, Jialiang Gong,Guoqin Huang, Yun Li

crossref(2024)

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摘要
Abstract The conversion of farmland to forest in China has been recognized for its positive impact on above-ground vegetation greening and carbon sequestration. However, the importance of soil functions in these conversion models, particularly in vulnerable karst areas, has received less attention. In this study conducted in a karst area of southwest China, eight different returning models (GM, GZ, ZI, TS, CM, AC, ZL) were investigated to assess soil carbon, nitrogen, and soil multi-functionality in the surface soil. The results showed significantly higher total carbon (TC), soil organic carbon (SOC), soil active organic carbon (AOC) and, ammonium nitrogen (AN) in afforestation land and abandonment land compared to grassland and maize crop area. Moreover, soluble organic carbon (DOC) was significantly higher in afforestation land and grassland compared to the maize crop area. Grassland and abandonment land exhibited significantly higher levels of NO3--N compared to afforestation land and maize crop. However, no significant difference in concentration of NH4+-N was found in afforestation land (except ZI) than between grassland and abandonment land. Regardless of soil multi-functionality or carbon and nitrogen multi-functional, afforestation land consistently exhibited significantly higher values than grassland. Pearson correlation analysis indicated positive correlations between soil indices and ecosystem multi-functionality (EMF), except for NO3--N.Random forest analysis, which explained 95% of the variation in soil EMF, identified the AOCL, SOC, TN, AN and TC as the main drivers of soil multi-functionality. In conclusion, different models of returning farmland have the potential to enhance soil nutrient accumulation and improve soil multi-functionality in karst areas. These findings highlight the effectiveness of such models for sustainable soil management and production.
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