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

摘要

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 degrees 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