Interactive effects of global change factors on soil respiration and its components: a meta-analysis.

As the second largest carbon (C) flux between the atmosphere and terrestrial ecosystems, soil respiration (Rs) plays vital roles in regulating atmospheric CO2 concentration ([CO2 ]) and climatic dynamics in the earth system. Although numerous manipulative studies and a few meta-analyses have been conducted to determine the responses of Rs and its two components [i.e., autotrophic (Ra) and heterotrophic (Rh) respiration] to single global change factors, the interactive effects of the multiple factors are still unclear. In this study, we performed a meta-analysis of 150 multiple-factor (≥2) studies to examine the main and interactive effects of global change factors on Rs and its two components. Our results showed that elevated [CO2 ] (E), nitrogen addition (N), irrigation (I), and warming (W) induced significant increases in Rs by 28.6%, 8.8%, 9.7%, and 7.1%, respectively. The combined effects of the multiple factors, EN, EW, DE, IE, IN, IW, IEW, and DEW, were also significantly positive on Rs to a greater extent than those of the single-factor ones. For all the individual studies, the additive interactions were predominant on Rs (90.6%) and its components (≈70.0%) relative to synergistic and antagonistic ones. However, the different combinations of global change factors (e.g., EN, NW, EW, IW) indicated that the three types of interactions were all important, with two combinations for synergistic effects, two for antagonistic, and five for additive when at least eight independent experiments were considered. In addition, the interactions of elevated [CO2 ] and warming had opposite effects on Ra and Rh, suggesting that different processes may influence their responses to the multifactor interactions. Our study highlights the crucial importance of the interactive effects among the multiple factors on Rs and its components, which could inform regional and global models to assess the climate-biosphere feedbacks and improve predictions of the future states of the ecological and climate systems.