Long-term effects of thinning on carbon storage in Cunninghamia lanceolata plantations
The stand environment and tree growth could be changed as well as carbon storage be affected by thinning.Thus it is important to conduct the research on changes of carbon stock in plantations after thinning for assessing the dynamics of forest ecosystem carbon pool.The carbon storage and its distribution of various components in 22-year-old Cunninghamia lanceolata plantations were studied with control and different treatments such as moderate and heavy thinning.Moderate (thinning intensity was 35％) and heavy (thinning intensity was 50％) thinning treatments were conducted twice at the age of 7 and 14 years,respectively.The stand of control was thinned 15％ in the 14th year.The results showed that the proportion of stem carbon storage increased with the increasing thinning intensity,while the proportion of carbon storage in branches,leaves and roots slightly decreased,which suggested that thinning was beneficial for carbon stocking in stem.However,the carbon storage in arbor layer decreased with the thinning intensity in C.lanceolata plantation under moderate and heavy thinning treatments,accounted for 89.0％ and 83.1％ of the control,respectively.The arbor carbon storage decreased in followed two years after the first thinning.The carbon storage in arbor layer had a fast recovery rate within eight years after the second thinning,and the increment of carbon storage in arbor layer had no difference with the control for the heavy thinning treatment.The carbon storage in understory vegetation,litter and soil layers also had no significant difference under the different thinning treatments.Generally total ecosystem carbon storage under the control,moderate and heavy thinning treatments reached 169.34,156.65 and 154.37 t · hm-2,respectively.There was no significant difference among the three treatments.Therefore,it could be concluded that the carbon storage in C.lanceolata plantation did not reduce after thinning in more than 15 years.
国家科技期刊平台
NSTL
万方数据
维普
