Improving Prediction of Heterotrophic Respiration in Response to Altered Precipitation

Abstract Soil heterotrophic respiration (Rh) is a key process in the global carbon (C) cycle, strongly influenced by interactions between soil temperature and moisture. It is well documented how soil temperature regulates Rh. However, temperature interacts with soil moisture to regulate Rh via dynamic and complex microbial mechanisms, leading to uncertainties in Rh prediction under altered precipitation. To address this knowledge gap, we conducted a field‐based rainfall manipulation experiment to investigate the effects of contrasting rainfall treatments (wet vs. dry) on Rh in root‐free soil across multiple seasonal campaigns. We then used the Dual Arrhenius and Michaelis‐Menten (DAMM) model to simulate Rh dynamics under both rainfall treatments. Our results showed that, on average, Rh was 13% higher in the wet treatment (mean: 1.32 μmol m −2 s −1 (range: 0.53, 2.37)) compared to the dry treatment (mean: 1.17 μmol m −2 s −1 (range: 0.40, 3.19)) across all campaigns. Soil temperature was the primary driver of Rh when sufficient soil moisture was available to support microbial activity. Soil temperature alone explained 46% of the variation in Rh under the wet treatment and 41% under dry. The DAMM model captured seasonal and treatment‐driven variation better in the wet than the dry treatment, explaining 80% and 42% of the variance in Rh, respectively. Model parameterization identified an intrinsic temperature sensitivity (Ea CO2 ) for Rh of 72.02 kJ mol −1 , with higher microbial basal respiration ( α CO2 ) values in wet soils, indicating enhanced microbial respiration under favorable moisture conditions. Our results demonstrate that shifts in rainfall regimes alter microbial respiration responses through complex moisture‐temperature interactions, which can be reliably captured using the DAMM model. This highlights the model's value for improving soil C feedback predictions under future climate scenarios.