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cje ›› 2009, Vol. 28 ›› Issue (12): 2417-2423.

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Effects of |Cunninghamia lanceolata plantations at different developmental stages on soil microbial community structure.

LIU Li1,2,3;DUAN Zheng-hu1|WANG Si-long2,3;HU Jiang-chun2; HU Zhi-gang2;ZHANG Qian-ru2;WANG Shu-jin2   

  1. 1Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China;2Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;3Huitong Experimental Station of Forest Ecology, Institute of Applied Ecology, Chinese Acade my of Sciences, Huitong 418307, Hunan, China
  • Online:2009-12-10 Published:2009-12-10

Abstract: By the method of denaturing gradient gel electrophoresis (DGGE), the polymorphism of soil bacterial 16S rRNA and fungal 28S rRNA specific fragments in 3-, 11-, 17-, 21-, and 24-year old Cunninghamia lanceolata plantations was studied, with the effects of  C. lanceolata plantation’s development stage on soil microbial community structure analyzed. The Shannon diversity index (H ) and richness (S) showed that the soil microbial community diversity increased significantly with the development of C. lanceolataplantation, but was still significantly lower than that in secondary broadleaved forests (P<0.05). Cluster analysis (UPGMA) indicated that the soil fungal community similarity in different aged C. lanceolata plantations was less than 60%, whereas that of soil bacterial community similarity was up to 65%, suggesting that the shift of soil fungal community structure with the development of C. lanceolataplantation was more obvious than that of soil bacterial community structure. The soil microbial diversity had significant correlations with soil available N content and C/N ratio (P<0.05). This study indicated that longterm silviculture with pure plantations could affect soil microbial community via altering soil properties, which in turn, could affect the nutrient cycling in forest ecosystem and the plantation productivity.

Key words: Coniferous forest, Change detection, Forest dynamics, Landsat TM, Mortality