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Litter decomposition determines soil organic matter (SOM) formation and plant‐available nutrient cycles. Therefore, accurate model representation of litter decomposition is critical to improving soil carbon (C) projections of bioenergy feedstocks. Soil C models that simulate microbial physiology (i.e., microbial models) are new to bioenergy agriculture, and their parameterization is often based on small datasets or manual calibration to reach benchmarks. Here, we reparameterized litter decomposition in a microbial soil C model (CORPSE ‐ Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment) using the continental‐scale Long‐term Inter‐site Decomposition Experiment Team (LIDET) dataset which documents decomposition across a range of litter qualities over a decade. We conducted a simplified Monte Carlo simulation that constrained parameter values to reduce computational costs. The LIDET‐derived parameters improved modeled C and nitrogen (N) remaining, decomposition rates, and litter mean residence times as compared to Baseline parameters. We applied the LIDET litter decomposition parameters to a microbial bioenergy model (Fixation and Uptake of Nitrogen – Bioenergy Carbon, Rhizosphere, Organisms, and Protection) to examine soil C estimates generated by Baseline and LIDET parameters. LIDET parameters increased estimated soil C in bioenergy feedstocks, with even greater increases under elevated plant inputs (i.e., by increasing residue, N fertilization). This was due to the integrated effects of plant litter quantity, quality, and agricultural practices (tillage, fertilization). Collectively, we developed a simple framework for using large‐scale datasets to inform the parameterization of microbial models that impacts projections of soil C for bioenergy feedstocks. 

Abstract Western US forests represent a carbon sink that contributes to meeting regional and global greenhouse gas targets. Forest thinning is being implemented as a strategy for reducing forest vulnerability to disturbance, including mortality from fire, insects, and drought, as well as protecting human communities. However, the terrestrial carbon balance impacts of thinning remain uncertain across regions, spatiotemporal scales, and treatment types. Continuous and in situ long‐term measurements of partial harvest impacts to stand‐scale carbon and water cycle dynamics are nonetheless rare. Here, we examine post‐thinning carbon and water flux impacts in a young ponderosa pine forest in Northern Idaho. We examine in situ stock and flux impacts during the 3 years after treatment as well as simulate the forest sector carbon balance through 2050, including on and off‐site net emissions. During the observation period, increases in tree‐scale net primary production (NPP) and water use persistence through summer drought did not overcome the impacts of density reduction, leading to 45% annual reductions of NPP. Growth duration remained constrained by summer drought in control and thinned stands. Ecosystem model and life cycle assessment estimates demonstrated a net forest sector carbon deficit relative to control stands of 27.0 Mg C ha⁻¹in 2050 due to emissions from dead biomass pools despite increases to net ecosystem production. Our results demonstrate dynamics resulting in carbon losses from forest thinning, providing a baseline with which to inform landscape‐scale modeling and assess tradeoffs between harvest losses and potential gains from management practices.