Microbial-explicit processes and refined perennial plant traits improve modeled ecosystem carbon dynamics

• DOI: 10.1016/j.geoderma.2024.116851
• Publication Date: 2024-03-11T12:03:20Z
• Authors: Danielle M Berardi; Melannie D. Hartman; Edward R Brzostek; Carl J. Bernacchi; Evan H. DeLucia; Adam C. von Haden; Ilsa Kantola; Caitlin E. Moore; Wendy H. Yang; Tara W. Hudiburg; William J. Parton
• Keywords: Biogeochemical Cycle; Soil carbon; Plant litter; Soil respiration

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, disturbance regimes. Understanding how soil dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions policy regarding net balance. Soil microbes play key role in both fluxes stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated processes into the DayCent model better represent large perennial grasses mechanisms formation We also take advantage recent improvements grass structural complexity life-history traits. Specifically, this study focuses on: 1) plant sub-model that represents phenology more refined chemistry with downstream implications for organic matter (SOM) cycling though litter inputs, 2) live dead microbe pools influence routing physically protected unprotected pools, 3) Michaelis-Menten kinetics rather than first-order decomposition calculations, 4) feedbacks between microbial pools. evaluated performance two SOM sub-models, (MM) (FO), using observations production, respiration, biomass, from long-term bioenergy research plots mid-western United States. The MM represented seasonal FO which consistently overestimated winter respiration. While sub-models were similarly calibrated total, protected, measurements, differed future response most notably Adding will improve predictions balances but data necessary validate change responses pool allocation.