Enhancing soil carbon sequestration may enable the bioenergy industry to improve greenhouse gas mitigation. To realize this potential, we must develop a predictive understanding of how management and feedstock decisions impact soil organic matter (SOM) formation. However, there remains uncertainty in how interactions between plant traits (i.e. litter chemistry, rhizosphere exudation) and microbial traits (i.e. carbon use efficiency (CUE), turnover) drive SOM formation for bioenergy feedstocks. To address this uncertainty, we incubated 13C-labelled leaf and root litter of three common bioenergy feedstocks, miscanthus, sorghum, and corn, in their corresponding field-conditioned soils in lab microcosms to follow the fate of litter inputs into microbial biomass, respiration, and SOM pools. In addition, we added simulated rhizosphere exudates to half of the mesocosms to test the extent to which rhizosphere processes altered the fate of litter inputs. We then used our estimates of CUE, turnover and protection rates to improve the parametrization of a novel-plant microbial interactions model, Fixation and Uptake of Nitrogen-Carbon, Organisms, and Rhizosphere Processes in the Soil Environment (FUN-CORPSE). Using this improved model, we ran simulations to examine the degree to which interactions between plant and microbial traits promoted SOM formation over thirty years of cultivation.
Results/Conclusions
In the lab, we found that corn and sorghum litter with low carbon to nitrogen ratios led to greater mineral-associated organic matter (MaOM) formation and less particulate organic matter (POM) formation than high carbon to nitrogen ratio, Miscanthus litter. This pattern reflected the enhancement of microbial carbon use efficiency, turnover, and necromass formation in microcosms with low carbon to nitrogen litters. However, exudate additions increased MaOM formation to a greater extent for Miscanthus litters, demonstrating a stronger reliance on rhizosphere processes when microbes are energy limited. When we integrated this data into FUN-CORPSE, we found that the improved model more accurately captured empirical differences between feedstocks in soil carbon stocks. In the thirty-year simulations, Miscanthus which relied more heavily on rhizosphere processes to gain nutrients had the greatest accumulation of soil carbon in both MaOM and POM pools. Collectively, these results highlight that integrating empirical data on plant and microbial traits into models enhances their ability to assess bioenergy sustainability.