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Effects of environmental factors on litter decomposition in arid and semi-arid regions: A review.

WANG Xin-yuan1,2, ZHAO Xue-yong1, LI Yu-lin1, LIAN Jie1,2, QU Hao1, YUE Xiang-fei1,2   

  1. (1Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China; 2Unversity of Chinese Academy of Sciences, Beijing 100049, China)
  • Online:2013-11-18 Published:2013-11-18

Abstract: Litter decomposition is one of the important biochemical processes in arid and semi-arid regions, and a key component of regional nutrient turnover and carbon cycling, which is mainly affected by climate, litter quality, and decomposer community. In order to deeply understand the relationships between litter decomposition and environmental factors in arid and semiarid regions, this paper summarized the research progress in the effects of abiotic factors (soil temperature, precipitation, and ultraviolet-B radiation) and biotic factors (litter quality, soil microbial and animal composition and community structure) on the litter decomposition in these regions. Among the factors, precipitation and ultraviolet-B radiation are considered to be the main limiting factors of litter decomposition. In arid and semi-arid regions, precipitation can significantly increase the litter decomposition rate in a short term, while the photo-degradation induced by ultraviolet-B radiation, due to the strong and long-term radiation, can increase the decomposition rate of terrestrial litter. Litter quality, soil microbial and animal composition and community structure are mainly affected by the type of ecosystems in a long term. However, the affecting mechanisms of these environmental factors on litter decomposition are still not very clear. It was suggested that the future litter ecological research should be paid more attention to the interaction of environmental factors under climate change, the variations of litter decomposition at different spatial scales, and the establishment of litter decomposition models in relation to the synergistic interactions of multiple factors.