Data from: Mycelia-derived C contributes more to nitrogen cycling than root-derived C in ectomycorrhizal alpine forests
Cite this dataset
Zhang, Ziliang et al. (2019). Data from: Mycelia-derived C contributes more to nitrogen cycling than root-derived C in ectomycorrhizal alpine forests [Dataset]. Dryad. https://doi.org/10.5061/dryad.kg17gq6
1. Plant roots and their associated microbial symbionts impact carbon (C) and nutrient cycling in ecosystems, but estimates of the relative contributions of root- versus microbe-derived dynamic inputs are highly uncertain. Roots release C into soil via exudation and turnover (i.e., root-derived C), but also by allocating C to mycorrhizal fungal mycelia, which exude C and undergo turnover (i.e., mycelia-derived C). Given that the relative contributions of root- and mycelia-derived C inputs are unknown, a key knowledge gap lies in understanding not only the relative contributions of root- versus mycelia-derived C inputs, but also the consequences of these fluxes on nutrient cycling. 2. Using ingrowth cores and stable isotope analyses, we quantified root- and mycelia-derived C inputs into the soil and their relative contributions to nitrogen (N) cycling in two ectomycorrhizal alpine forests, a 70-year-old spruce plantation and a 200-year-old spruce-fir dominated forest, in western Sichuan, China. 3. Across the two forests, extramatrical mycelia of ectomycorrhizal fungi accounted for up to two-thirds of the new root C inputs into soil and ~80% of the stimulated N mineralization. Moreover, flux-specific (per gram) mycelia-derived C inputs stimulated multiple indices of soil N cycling to a greater degree than the flux-specific root-derived C inputs, accounting for ~70% of the stimulated N mineralization in both forests. 4. Collectively, our findings indicate that the effects of mycorrhizal fungi on soil C and N cycling may exceed those of roots in alpine coniferous forests dominated by ectomycorrhizal fungi, highlighting the need to incorporate mycorrhizal fungal inputs into biogeochemical models for ecosystems.