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Interactive effects of grazing and global change factors on soil and ecosystem respiration in grassland ecosystems: A global synthesis

70

Citations

29

References

2019

Year

Abstract

Abstract As the key carbon (C) fluxes between biosphere and atmosphere, soil respiration ( R s ) and ecosystem respiration ( R e ) play vital roles in regulating global C balance and climate‐biosphere feedback in the Earth system. Despite the fact that numerous manipulative studies and a few meta‐analyses have been conducted to examine the responses of R s and its components (i.e. autotrophic [ R a ] and heterotrophic respiration [ R h ]) as well as R e to grazing (G) or global change factors, the interactive effects between grazing and global change factors remain poorly understood. Here, we performed a comprehensive meta‐analysis of manipulative experiments with both grazing and global change factors to quantify their individual and interactive effects on R s and its components as well as R e . Our results showed that grazing and drought significantly decreased R s by 12.35% and 20.95%, respectively, whereas warming (W), nitrogen addition (N) and increased precipitation (P) stimulated it by 2.12%, 5.49% and 13.44%, respectively. Similarly, grazing, warming, nitrogen addition and increased precipitation increased R e by 7.21%, 4.94%, 48.45% and 21.57%, respectively, while drought decreased it by 16.86%. However, the combinations of grazing with warming (GW), nitrogen addition (GN) and increased precipitation (GP) exhibited non‐significant effects on R s . More importantly, additive interactions between grazing and global change factors exhibited a substantial predominance on R s , R a , R h and R e rather than synergistic and antagonistic ones. Synthesis and applications . Our findings highlight the crucial importance of the interactive effects between grazing and global change factors on soil respiration ( R s ) and ecosystem respiration ( R e ). Therefore, incorporating this key influence on ecosystem processes into Earth system models (ESMs) could better improve the prediction of climate‐biosphere feedbacks and develop sustainable strategies for grassland management in the Anthropocene.

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