Reevaluating multi-pool first-order kinetic models for fitting soil incubation data

Abstract

Soil incubation experiments are frequently conducted to investigate soil carbon (C) cycling and its response to environmental changes. Multi-pool first-order models, which apply constant kinetic rate parameters for each pool, are widely used for fitting these datasets due to their simplicity. However, their ability to accurately represent instantaneous C effluxes is often overlooked, as cumulative effluxes are typically prioritized. Here, we calibrated a three-pool first-order model using a 384-day incubation dataset with fluctuating CO₂ and CH₄ effluxes. Despite constantly good performance for cumulative C effluxes (R² = 0.99–1.00), the R² values vary greatly with experimental conditions for instantaneous effluxes (R² = 0.36–0.93), depending on the frequency of aerobic-anaerobic shifts. The results are regardless of the objective function used for model fitting (i.e., maximizing R² for instantaneous or cumulative C effluxes). Compared to cumulative effluxes, we propose emphasizing instantaneous effluxes and calibrating additional variables in soil C modeling. This strategy can offer more insights for improving predictions and enhancing understanding of soil C-climate feedbacks under dynamic environmental conditions.