| 02 Dec 2025
Drought-Induced Soil Carbon Dynamics in Subtropical Forests: Emergent Divergence from Model Structures
Abstract. Accurately quantifying drought impacts on terrestrial carbon cycling is essential for advancing predictions of climate-carbon feedbacks. However, current biogeochemical models exhibit limited capability in simulating drought-induced transformations of soil organic carbon (SOC), particularly regarding microbial processes. Here, we conducted a systematic comparative evaluation of three prevailing SOC modeling structures, including conventional three-pool partitioning scheme (SM1), mineral and particulate- associated carbon partitioning scheme (SM2) and Michaelis-Menten regulated carbon-stabilization scheme (SM3), to elucidate their capacity in simulating soil carbon dynamics under decadal drought scenarios in a subtropical forest. We found divergent effects of drought in soil C input (SM1, 66%; SM2, 10%; SM3, -4%) and mean residence time (MRT; SM1, -31%; SM2, -14%; SM3, 65%), which lead to the predicted SOC substantial accumulation for both SM1 and SM3 (+39.5% and +56.9%, respectively) and moderate depletion (-6.1%) for SM2. The different C input directly affect the passive SOC (SM1) and mineral-associated organic carbon (SM2 and SM3). In comparison, the drought effects on passive SOC (SM1), microbe biomass (SM2) and MAOC (SM2 and SM3), lead to notable spread in MRT. These findings highlight critical model structural dependencies in simulating drought-affected soil carbon dynamics and emphasize the necessity for models to integrate microbial-physicochemical interactions for improved climate-carbon coupling projections.
This work addresses a critical question in models: how different model structures simulate soil carbon responses to drought. The integration of long-term experimental data from the Tiantong Forest with a multi-model comparison and traceability analysis is a clear strength of the manuscript. Below, I offer some feedback aimed at further strengthening the scientific novelty and rigor of this manuscript.
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First, the introduction effectively establishes the problem but could more sharply define the specific knowledge gap that this study uniquely fills. It stated that models have limited capability and studies are scarce, but what is the conceptual novelty? I think the authors need to convey the message: how does this comparison of different model structure actually contribute to our capability to more accurately/realistically simulate SOC responses to drought?
Second, is it possible to illustrate some details of the vegetation model? It does seem that coupling of the vegetation model with the three different soil modules is a significant undertaking worths of highlighting. The flexibility of this vegetation model is a strength. So I would recommend some brief text about the coupling.
Third, Â the differences between models are clear qualitatively. Is it possible to add a simple metric to quantitatively underscore the magnitude of model-structure-induced uncertainty? This could be a powerful summary statistic.
Fourth, in the discussion sections, is it possible to discuss what these divergences imply for future model development and large-scale projections? Should all terrestrial models move towards SM2/SM3 structures for drought simulation? What are the trade-offs (complexity, data needs, computational cost)?