文献类型：期刊文献

英文题名：Forest carbon storage in China from 2003 to 2021: Estimation based on the volume-derived carbon storage model with scale-compatible and tree species-merged

作者：Zhang, Cong[1,2] Li, Haikui[1,2] Wang, Xiaohui[1,3] Liu, Pengju[1,2] Liu, Qi[1,2] Zhan, Siying[1,2]

第一作者：Zhang, Cong

通信作者：Li, HK[1];Liu, PJ[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]State Forestry & Grassland Adm, Key Lab Forest Management & Growth Modelling, Beijing 100091, Peoples R China;[3]Natl Forestry & Grassland Adm, Key Lab Forestry Remote Sensing & Informat Syst, Beijing 100091, Peoples R China

年份：2025

卷号：578

外文期刊名：FOREST ECOLOGY AND MANAGEMENT

收录：;EI(收录号：20245217592585);Scopus(收录号：2-s2.0-85212961216);WOS:【SCI-EXPANDED(收录号:WOS:001394670300001)】；

基金：This work was supported by the National Key Research and Devel-opment Program of China [Grant No. 2021YFD2200404] ; and National Natural Science Foundation of China [Grant No. 42141004] .

语种：英文

外文关键词：Forest carbon storage; Uncertainty; Volume-derived carbon storage model; Scale-compatible; Tree species-merged

摘要：Accurately estimating and assessing the forest carbon storage in China is crucial to achieving the carbon peak and neutrality targets. In this paper, utilizing data from 173,031 plots obtained during China's 6-9th national forest inventory, we established a volume-derived forest carbon model based on scale-compatible and tree speciesmerged method. Utilizing the statistical data of forest area and volume from 2003 to 2021, we estimated and evaluated the national forest carbon storage, and analyzed the spatial and temporal distribution of forest carbon. We also analyzed the uncertainty of national forest carbon storage and recommended a more suitable forest carbon storage estimation model. Our study indicated that: (1) Determination coefficients (R-2), standard error of estimate (SEE) and mean prediction error (MPE) for the population average model were 0.964, 5.85 t/ha, and 0.60 %, respectively. The model we have established was better and can be applied to estimate and evaluate the national forest carbon storage. (2) When all plots were used as modeling units, the R-2, SEE and MPE of the scalecompatible model were 0.914, 10.69 t/ha and 0.13%, respectively, while the tree species-merged method had a better fit, with the R-2, SEE and MPE of 0.960, 7.26 Mg ha(-1) and 0.09%, respectively. (3) From 2003-2021, the forest carbon storage in China increased rapidly, from 4.96 +/- 0.25 Pg C in 2003-7.95 +/- 0.40 Pg C in 2021, with an average annual carbon sink of 0.166 Pg C/yr. Forest carbon storage was mainly distributed in the southwest and northeast, and was also mainly stored in Pinaceae. It is worth noting that from 2003 to 2013, hard broadleaved forest played a role as a carbon source due to the sharp decrease in area. (4) The average uncertainty of national forest carbon storage estimated by the tree species-merged method was 5.05 %, and the minimum was only 5.03 %. Compared with the most detailed model (a provincial-scale model with distinguishing dominant tree species group and stand characteristics), the estimation error of forest carbon storage in the simplest model (a national-scale model without distinguishing forest level and stand characteristics) was less than 5 %. Therefore, we recommended that the simplest model can be used to estimate the national forest carbon storage. The forest carbon storage model proposed in this paper can provide support for accurately estimating and evaluating forest carbon storage in China.