文献类型：期刊文献

英文题名：How large is the difference in large-scale forest biomass estimations based on new climate-modified stand biomass models?

作者：He, Xiao[1] Lei, Xiang-Dong[1] Dong, Li-Hu[2]

第一作者：He, Xiao

通信作者：Lei, XD[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Key Lab Forest Management & Growth Modelling, State Forestry & Grassland Adm, Beijing 100091, Peoples R China;[2]Northeast Forestry Univ, Sch Forestry, Key Lab Sustainable Forest Ecosyst Management Min, Harbin 150040, Heilongjiang, Peoples R China

年份：2021

卷号：126

外文期刊名：ECOLOGICAL INDICATORS

收录：;EI(收录号：20211510196973);Scopus(收录号：2-s2.0-85103773288);WOS:【SCI-EXPANDED(收录号:WOS:000647801300005)】；

基金：This research was supported by the Forestry Public Welfare Scientific Research Project (grant No. 201504303) and the National Natural Science Foundation of China (Grant Nos. 31270679, 31800539) .

语种：英文

外文关键词：Climate-sensitive stand biomass model; Forecast combination; Model uncertainty; Carbon service

摘要：Accurate forest carbon service accounting is essential for climate change mitigation. At present, the knowledge about whether and how climate-sensitive stand biomass models could reduce the uncertainty of forest biomass/ carbon estimation is lacking. Hence, the aim of this study is to develop climate-sensitive stand biomass models and quantify their differences. Data containing 539 sample plots of larch plantations in northern and northeastern China were utilized to develop two basic and the corresponding climate-sensitive stand biomass models. Owing to the uncertainty from predictors, the forecast combination method was used to combine the two basic models (FCMs) and the two climate-sensitive models (CS-FCMs) and to quantify the difference in biomass estimations at the plot and regional scales. Results showed that the adjusted R2 values of the stand biomass models were greater than 0.85 and the relative root mean square errors ranged from 5.51% to 22.62%. The CS-FCMs produced more accurate biomass estimates than the FCMs. The difference in biomass estimations derived from biomass models with and without climatic variables was 411,549 tons or 0.27% at the regional scale, but the carbon value difference amounted to about $8.3 million. This study underlined the importance of accurate carbon accounting based on climate-modified stand biomass models for forest carbon management.