Ammonia oxidation is the first and rate-limiting step of nitrification and is performed by both ammoniaoxidizing archaea (AOA) and bacteria (AOB). However, the environmental drivers controlling the abundance, composition, and activity of AOA and AOB communities are not well characterized, and the relative importance of these two groups in soil nitrification is still debated. Chinese tea orchard soils provide an excellent system for investigating the long-term effects of low pH and nitrogen fertilization strategies. AOA and AOB abundance and community composition were therefore investigated in tea soils and adjacent pine forest soils, using quantitative PCR (qPCR), terminal restriction fragment length polymorphism (T-RFLP) and sequence analysis of respective ammonia monooxygenase (amoA) genes. There was strong evidence that soil pH was an important factor controlling AOB but not AOA abundance, and the ratio of AOA to AOB amoA gene abundance increased with decreasing soil pH in the tea orchard soils. In contrast, T-RFLP analysis suggested that soil pH was a key explanatory variable for both AOA and AOB community structure, but a significant relationship between community abundance and nitrification potential was observed only for AOA. High potential nitrification rates indicated that nitrification was mainly driven by AOA in these acidic soils. Dominant AOA amoA sequences in the highly acidic tea soils were all placed within a specific clade, and one AOA genotype appears to be well adapted to growth in highly acidic soils. Specific AOA and AOB populations dominated in soils at particular pH values and N content, suggesting adaptation to specific niches.
Central banks worldwide have started researching and developing central bank digital currencies (CBDCs). In the digital economy context, concerns regarding the integrity, competition, and privacy of CBDC systems have also gradually emerged. Against this backdrop, this study aims to evaluate users’ willingness to use China’s digital currency electronic payment (DCEP) system, a digital payment and processing network, and its influencing factors by comprehensively considering and comparing the characteristics of cash and third-party payment services. Combining the push-pull-mooring framework (PPM) and task-technology fit (TTF) theory, we discuss the scenarios and mechanisms that may inspire users’ DCEP adoption intention through an empirical study. The results reveal that privacy concerns regarding the original payment methods and technology-task fitting level of DCEP positively impact users’ willingness to adopt DCEP. The technical characteristics of DCEP, users’ payment requirements, and government support positively affect users’ adoption intention by influencing the task-technology fitting degree of DCEP. Switching cost significantly and negatively impacts adoption intention, whereas relative advantage exhibits no significant effect. This research contributes to a better understanding of the factors that influence switching intentions and the actual use of DCEP, and provides policy guidance on promoting the efficiency and effectiveness of DCEP.
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