Environmental Drivers and Spatial-Temporal Estimation of Precipitation Change Effects on Soil Respiration at the Global Scale

Soil respiration (Rs) is defined as the emission of carbon dioxide from soil into the atmosphere, which represents a critical carbon flux within terrestrial ecosystems. Precipitation change significantly influences Rs, generating feedback mechanisms pertinent to global climate change. Nevertheless, the global distribution and environmental determinants of precipitation's effects on Rs remain uncertain. We compiled a database encompassing 570 Rs observations from field experiments that manipulated precipitation, derived from 221 published studies. Utilizing this comprehensive data set, we conducted a meta-analysis to elucidate Rs responses to precipitation alterations. Subsequently, we employed a machine learning approach to provide a globally spatially explicit quantification of precipitation change effects on Rs under future climate scenarios. Our findings revealed that increased experimental precipitation markedly enhances Rs, while decreased precipitation inhibits it. Furthermore, Rs responses to precipitation change exhibited variability across ecosystems and climatic regions. This study also confirmed that the Rs responses vary based on the intensity and duration of precipitation change, with short-term or heavy precipitation fluctuations exerting the strongest effects. Environmental conditions influenced the reaction of Rs to precipitation change, as factors such as soil type, vegetation, and climate worked together to mediate spatial differences. Projections based on bioclimatic predictors suggest that future climate scenarios significantly amplify Rs responses to precipitation change, potentially increasing uncertainties in greenhouse gas emissions estimates. Overall, our analysis emphasizes the significance of context dependencies and offers a spatially explicit assessment of precipitation change impacts on Rs on a global level, providing a comprehensive reference for comprehending ecosystem carbon dynamics.