• 论文与研究报告 •

### 模型和林分因子对区域尺度碳计量参数的影响——以杉木为例

1. 1. 中国林业科学研究院资源信息研究所 北京 100091;
2. 国家林业局调查规划设计院 北京 100714
• 收稿日期:2016-03-23 修回日期:2016-09-28 出版日期:2017-09-25 发布日期:2017-10-24
• 基金资助:
国家自然科学基金项目（31370634）；中国清洁发展机制基金赠款项目（2013014）。

### Effects of Model and Stand Factors on the Parameters to Carbon Accounting at the Regional Scale——a Case Study for Cunninghamia lanceolata

Li Haikui1, Ou Qiangxin1, Zhao Jiacheng1, Yang Ying2, Quan Feng1

1. 1. Research Institute of Forest Resource Information Techniques, CAF Beijing 100091;
2. Academy of Forestry Inventory and Planning, State Forestry Administration Beijing 100714
• Received:2016-03-23 Revised:2016-09-28 Online:2017-09-25 Published:2017-10-24

Abstract: [Objective] In order to provide scientific and reasonable parameters and estimation method for estimating the carbon storage of arbor forests at the regional scale, the effects of model and forest factors on biomass carbon storage transformation and expansion coefficient (BCCEF) were studied.[Method] Taking Cunninghamia lanceolata as an example, thinking the permanent sample plots in Fujian, Jiangxi, Hunan and Guangdong provinces as four blocks, multi-ways analysis of variance were carried out to determine the most stable model. The factors included the selection of regional models or foreign models, the expansion ways from tree-level to regional scale with the independent model or the compatibility model with volume and the models with one or two variables. Then, six stand factors, which are two qualitative factor, stand origin and age group and four quantitative factors, mean DBH(diameter at breast height), mean height, breast height basal area and stand density, were selected to conduct backward stepwise regression and analysis of variance with interaction. At last, the stand factors, which had significant influences on the parameters to carbon accounting at regional scale were screened out.[Result] Expansion way and the selection of models had significant effects on two parameters to carbon accounting, the parameter estimated by independent model was greater than that estimated by the compatibility model with volume, and model selection could cause 8%-17% of parameters error. The number of model variables had a significant influence on biomass carbon conversion and expansion factors for root part(BCCEFR), but had no significant effect on biomass carbon conversion and expansion factors for aboveground part(BCCEFA). Stand origin had a significant effect on two parameters to carbon accounting, and the parameter for natural forest was greater than that for plantation. Age group had a significant influence on BCCEFA and minor effect on BCCEFR,the parameters for BCCEFA basically showed a declining trend from young forest to over-mature forest. The mean height, stand density and breast height basal area had significant effects on two parameters to carbon accounting with more influences on BCCEFR than BCCEFA. Among these factors, the mean height, stand density and the two parameters showed negative correlations, and breast height basal area and the two parameters were positively correlated. The mean DBH had minor effect on the parameters. Except for total BCCEFR, the differences of the two parameters grouped by stand origin and age group and total BCCEFA between Hunan and Guangdong provinces, in which a same regional biomass model was used, were no significant. Similarly, the differences of two total parameters and the two parameters grouped by stand origin and age group between Fujian and Jiangxi provinces were significant.[Conclusion] The two total parameters to carbon accounting, estimated by the model compatible with volume and the model with two variables and regional model, are most stable. Stand origin, age group, the mean height, stand density and breast height basal area have significant effects on the parameters to carbon accounting. Even if using a same regional model, the differences of stand factors between provinces may lead to significant differences in the parameters to carbon accounting.