Limitations of 2-pool models in representing different time-scale dynamics of particulate and mineral-associated organic carbon

Abstract. In the last decade, the conceptual framework that characterizes soil organic carbon (SOC) into particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) fractions has gained traction in studies of C dynamics. This SOC characterization is useful for developing empirical studies and for parsimonious model parameterizations. However, rigorous testing of model structures incorporating the POC-MAOC framework is still lacking, in particular tests involving simultaneous measurements of C pool changes and respiration fluxes. We conducted an incubation experiment using control and litter-addition treatments, measuring changes in SOC fraction contents and respiration fluxes throughout the incubation. Then, we applied an inverse modelling approach to compare the performance of 2-pool (POC-MAOC) and 3-pool models (which also included a faster-cycling litter C pool) to reproduce the observed data. We then calculated the C ages and transit times to explore the predicted C persistence. Finally, we performed simulations to evaluate the effects of different model structures and parameterizations on SOC persistence. For both treatments, we observed that 2-pool models were unable to simultaneously reproduce the changes in C pool contents and respiration, while the 3-pool models adequately predicted both variables and yielded lower C ages and transit times. The fact that 3-pool models outperformed 2-pool models even for control soils, indicates that POC represents a heterogeneous pool that should be modelled as distinct compartments. We discuss that 2-pool models collapse POC dynamics operating at different timescales into a single one, failing to capture the different respiration phases and the gradual C pool changes. In contrast, 3-pool models distributed C processes operating at different timescales among compartments: the litter C pool captured faster-cycling dynamics, allowing POC and MAOC to better represent intermediate- and long-term dynamics, respectively. We also found that both model structure and changes in key parameters affected C persistence estimations. Models that included shorter pathways to MAOC, or allowed faster transfers into more persistent pools, predicted higher C age and transit time. This study highlights the limitations of representing SOC dynamics exclusively through POC and MAOC and shows how model structure shapes SOC contents and persistence estimates. Rather than advocating a specific model configuration, our results suggest that SOC models should explicitly represent processes operating across multiple timescales, which, depending on the ecosystem context, may require incorporating additional C compartments beyond the POC-MAOC framework. Furthermore, as transfer rates play a key role in determining SOC persistence, it is important to better understand and quantify how C is transferred toward MAOC and how these processes can be represented in models.