Absorptive roots outweigh transport roots in modulating nitrogen-addition effects on soil organic carbon accumulation in a subtropical forest

• We separated the rhizosphere of absorptive roots (ARs) and transport roots (TRs). • Nitrogen (N) addition promoted SOC accumulation influenced by both ARs and TRs. • ARs outweigh TRs in modulating N-addition effects on SOC accumulation. • Mechanisms driving N-induced SOC accumulation differ between ARs and TRs. Root carbon (C) inputs play a pivotal role in mediating the formation, accumulation, and turnover of soil organic C (SOC). However, how different root functional modules (absorptive roots [ARs] vs. transport roots [TRs]) regulate SOC dynamics under elevated atmospheric nitrogen (N) deposition remains unclear. By separately collecting rhizosphere soils of ARs and TRs and quantifying SOC accumulation therein, we characterized the distinct roles of these two root modules in regulating SOC dynamics in a subtropical karst forest subjected to different rates of N additions. Nitrogen addition promoted SOC accumulation in the rhizosphere of both ARs and TRs, especially at higher N-addition rate. Moreover, the rhizosphere SOC contents of ARs were significantly higher than those of TRs across N-addition treatments. Correlation analysis indicated that under the influence of ARs, SOC content was significantly and positively correlated with both protective mineral-associated SOC poos and microbial carbon pump (MCP) efficacy. By contrast, in the context of TRs, a significantly positive association was observed exclusively between SOC content and protective mineral pools, with no significant correlation of SOC content with MCP efficacy. These findings suggest that ARs outweigh TRs in mediating the effects of N addition on SOC accumulation. Mechanisms driving N-induced SOC accumulation may differ between two root functional modules, with each module governing distinct regulatory pathways. This study highlights the necessity to integrate root functional traits, particularly those distinguishing ARs and TRs, into process-based predictive frameworks of ecosystem C cycling. Such integration is critical for improving the mechanistic understanding and predictive accuracy of soil C dynamics in the context of projected N deposition regimes.