Absorptive and transport roots differ in terms of their impacts on rhizosphere soil carbon storage and stability in alpine forests

The fine roots of woody plants can be classified as absorptive roots and transport roots based on their distinct morphological, physiological, and functional traits. The potential ecological consequences of roots with different functional classifications on soil biogeochemical processes have been widely recognized. However, the magnitude of rhizosphere soil C stocks and the associated C stabilization mechanisms driven by these two root functional modules remain unknown. We quantified the soil organic C (SOC) contents and the C fractions in the rhizospheres of absorptive and transport roots in mineral soil in a spruce (Picea asperata Mast.) plantation and further estimated the rhizosphere SOC stocks of the two root functional modules by establishing a numerical model based on the extent of the rhizosphere. We also determined the characteristics of the SOC chemistry and metal-organic complexation in the rhizosphere to distinguish how the two root functional modules differentially impact rhizosphere SOC stability. The SOC content of the rhizosphere of absorptive roots was 15.7% higher than that of the rhizosphere of transport roots. This result can be mainly attributed to the higher stability of SOC (i.e., chemical recalcitrance and metal-organic bond) in the rhizosphere of absorptive roots. The numerical model analysis showed that the rhizosphere SOC pool of absorptive roots (0.27-2.7 kg C/m2) was twice as large as that of transport roots (0.18-1.36 kg C/m2). The contribution of the rhizosphere SOC stock of absorptive roots (63.5%) to the total rhizosphere SOC accrual was much higher than that of the rhizosphere SOC stock of transport roots (36.5%) in the scenario with a 1-mm extent. The rhizosphere soil C stock of absorptive roots plays a predominant role in the total rhizosphere soil C stock in alpine coniferous forests. Our findings highlight the importance of integrating function-based fine root classifications with rhizosphere soil C storage into land surface models of C cycling, which would be instrumental for accurately predicting soil C dynamics in alpine coniferous forest ecosystems.