Different responses of soil respiration and its components to nitrogen addition among biomes: a meta-analysis

Anthropogenic activities have increased nitrogen (N) deposition by threefold to fivefold over the last century, which may considerably affect soil respiration (Rs). Although numerous individual studies and a few meta-analyses have been conducted, it remains controversial as to how N addition affects Rs and its components [i.e., autotrophic (Ra) and heterotrophic respiration (Rh)]. To reconcile the difference, we conducted a comprehensive meta-analysis of 295 published studies to examine the responses of Rs and its components to N addition in terrestrial ecosystems. We also assessed variations in their responses in relation to ecosystem types, environmental conditions, and experimental duration (DUR). Our results show that N addition significantly increased Rs by 2.0% across all biomes but decreased by 1.44% in forests and increased by 7.84% and 12.4% in grasslands and croplands, respectively (P < 0.05). The differences may largely result from diverse responses of Ra to N addition among biomes with more stimulation of Ra in croplands and grasslands compared with no significant change in forests. Rh exhibited a similar negative response to N addition among biomes except that in croplands, tropical and boreal forests. Methods of partitioning Rs did not induce significant differences in the responses of Ra or Rh to N addition, except that Ra from root exclusion and component integration methods exhibited the opposite responses in temperate forests. The response ratios (RR) of Rs to N addition were positively correlated with mean annual temperature (MAT), with being more significant when MAT was less than 15 °C, but negatively with DUR. In addition, the responses of Rs and its components to N addition largely resulted from the changes in root and microbial biomass and soil C content as indicated by correlation analysis. The response patterns of Rs to N addition as revealed in this study can be benchmarks for future modeling and experimental studies.