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江西杉木人工林生物量分配格局及其模型构建(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2016年03期
Page:
177-182
Column:
研究简报
publishdate:
2016-05-18

Article Info:/Info

Title:
Biomass allocation and its model construction of Cunninghamia lanceolata plantations in Jiangxi Province
Article ID:
1000-2006(2016)03-0177-06
Author(s):
ZENG Wei1 JIANG Bin2 YU Lin1 XIAO Fuming1* XU Haining1
1.Jiangxi Academy of Forestry, Nanchang 330032,China;
2. Yongfeng County Guanshan Forest Farm of Jiangxi Province, Yongfeng 331506,China
Keywords:
Cunninghamia lanceolata plantation forest age allocation pattern biomass model Jiangxi Province
Classification number :
S718
DOI:
10.3969/j.issn.1000-2006.2016.03.029
Document Code:
A
Abstract:
In order to study the dynamic biomass allocation pattern and their accurate estimation methods of Cunninghamia lanceolata plantations in Jiangxi Province, biomass data at different stand ages were analyzed at the provincial scale. Biomass of C. lanceolata plantations in Jiangxi Province ranged from 55.64 to 165.22 t/hm2, and biomass at tree layer accounted for more than 94.2%. The biomass of C. lanceolata plantations and their tree layers increased with the increasing of age at first, then decreased. The biomass at shrub layer, herb layer or litter had no significant differences among all different ages. The permutation orders of biomass of each components in young, premature and mature plantations were followed as tree layer > litter layer > shrub layer > herb layer. However, the permutation orders in middle-aged and overage plantations were followed as tree layer > litter layer > herb layer > shrub layer. The permutation order of biomass of each organs in young plantation were followed as trunk > leaf > root > branch, but the permutation orders in other four plantations were followed as trunk > root > branch> leaf. The predicted values by the both an individual biomass model(W=0.266D2.069), which was based on the independent variable diameter at breast height(D), and a double variable model(W=0.046 9(D2H)0.906 4), which was based on the diameter at breast height(D)and height(H), were all less than the measured values. The prediction accuracy of the two models(R2)were all 0.84, and lower than 0.91 of a three variable model(W=11.497D1.847A0.082N-0.478)which was based on the diameter at breast height(D), age(A)and density(N).

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Last Update: 2016-06-30