Tree roots and their fungal symbionts mediate the response of rhizosphere soil organic carbon (SOC) decomposition to climate warming, specifically the temperature sensitivity of soil microbial respiration (Q10), which is a critical parameter for projecting the magnitude of terrestrial soil C-climate feedbacks. However, the intensity of the rhizosphere effects (RE; rhizosphere soils vs. bulk soils) on Q10 in forest soils associated with different mycorrhizal groups and their seasonal dynamics are poorly understood. Here, we selected nine tree species associated with either arbuscular mycorrhizal (AM) or ectomycorrhizal (EM) fungi in subtropical forests of China and collected bulk soil and rhizosphere soil in both the warm and cold seasons to explore the RE on Q10, respectively. Our results showed a positive RE on Q10 (ranging from 20.1% to 87.5%) for all tree species, independent of the season. For EM tree species, the RE on Q10 was 64.5% higher in the warm season and 44.4% higher in the cold season, compared to AM tree species. The RE on Q10 of AM and EM tree species was 44.8% and 65.0% larger in the warm season than that in the cold season, respectively. Fine root traits (including biomass, the carbon to nitrogen ratio, and soluble sugar content) predominantly controlled the RE on Q10 in AM-dominated forests, whereas the RE on soil properties (such as NH4+ and C availability) dominantly governed the RE on Q10 in EM-dominated forests. Furthermore, the RE on Q10 was also positively correlated with the RE on soil microbial phospholipid fatty acids in both AM- and EM-dominated forests. These findings suggest that rhizosphere soils in EM-dominated forests are more susceptible to C losses under climate warming than those in AM-dominated forests, compared to their respective bulk soils, potentially limiting rhizosphere SOC sequestration. The greater vulnerability of EM-dominated forests underscores the importance of accounting for root-soil interactions, mycorrhizal associations, and seasonal dynamics in C-climate models to improve predictions of SOC cycling and its feedback to global warming.