A global dataset of soil organic carbon mineralization under various incubation conditions

Abstract. Microbial decomposition of soil organic carbon (SOC) is a major source of atmospheric CO₂ and a key component of climate-carbon feedbacks. Understanding how SOC mineralization responds to temperature is essential for improving climate projections. Here, we compiled a global dataset of laboratory incubation experiments measuring SOC mineralization across diverse soils and temperature regimes. The dataset reveals that 84 % of samples originated from surface soils (0–30 cm), and 50 % of incubations lasted fewer than 50 days. Incubation temperatures ranged from –10 to 60 °C, with temperature intervals used to estimate temperature sensitivity (Q₁₀) spanning 2–40 °C; notably, 81 % of Q₁₀ estimates were based on intervals exceeding 5 °C. Moreover, in 61 % of cases, the lower incubation temperature for Q₁₀ estimation differed from the mean annual temperature at the sampling site by more than 5 °C, indicating a mismatch with in situ conditions. Our analysis highlights critical gaps in current experimental designs, particularly the underrepresentation of subsoils (>30 cm) and the use of temperature ranges that deviate from field conditions. We further evaluated the ability of 16 temperature response functions used in 69 Earth System Models to capture SOC mineralization patterns. Most models failed to reproduce empirical temperature response, especially at higher temperatures, albeit multi-term exponential functions showed relatively better performance. By coupling our dataset with a two-pool carbon model, we found that external environmental constraints and the intrinsic temperature response (including SOC decomposability and microbial processes) similarly influence the temperature sensitivity of SOC mineralization at the global scale, with their relative importance varying across ecosystem types. Our findings underscore the need for incubation experiments that better represent field conditions—both in depth and temperature range—and call for improved model parameterizations to enhance SOC feedback projections under future climate scenarios. The dataset is archived and publicly available at https://doi.org/10.6084/m9.figshare.25808698 (Zhang et al., 2025).