文献类型：期刊文献

英文题名：The performance of 3-PG model in Chinese fir plantations with different initial densities in southern China

作者：Nie, Wen[1,2] Liu, Jianfeng[1] Wang, Qi[1] Huang, Ruizhi[1,2] Zhao, Yipei[1] Yang, Shaowei[1] Sun, Jingyi[1] Xiao, Wenfa[2] Duan, Aiguo[1] Xiao, Yihua[3] Wang, Zuyuan[4]

第一作者：Nie, Wen

通信作者：Liu, JF[1];Xiao, YH[2]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, State Key Lab Efficient Prod Forest Resources, Beijing 100091, Peoples R China;[2]Chinese Acad Forestry, Ecol & Nat Conservat Inst, Key Lab Forest Ecol & Environm Natl Forestry & Gra, Beijing 100091, Peoples R China;[3]Chinese Acad Forestry, Res Inst Trop Forestry, Guangzhou 510520, Peoples R China;[4]Swiss Fed Res Inst WSL, CH-8903 Birmensdorf, Switzerland

年份：2024

卷号：495

外文期刊名：ECOLOGICAL MODELLING

收录：;EI(收录号：20242716646579);Scopus(收录号：2-s2.0-85197152834);WOS:【SCI-EXPANDED(收录号:WOS:001266844900001)】；

基金：This study was supported by the 14th Five Year Plan for Key Research and Development of China (2022YFF130180101) and the Fundamental Research Funds for the Central Nonprofit Research Institution of CAF (CAFYBB2022ZA001) . We extend our thanks to the re- viewers for their careful reading and helpful comments on this manuscript.

语种：英文

外文关键词：Chinese fir; Forest growth model; 3-PG model; Initial planting density; Self-thinning

摘要：Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most widely distributed conifer species in the subtropical region of southern China. Due to its ecological and economic significance, accurate prediction of growth of Chinese fir plantations is crucial for forest management and industrial timber production. In this study, we employed a physiologically process-based model (3-PG) to simulate the growth dynamic of Chinese fir plantations under various initial planting densities in southern China. Calibration and validation results indicated that the model outputs have strong correlations with the observed data (R-2 > 0.79, p < 0.01), except foliage biomass and root biomass. Self-thinning will occur earlier at higher initial planting densities, and stand DBH and height will increase dramatically afterwards. Sensitivity analysis further revealed that the FR (soil fertility rating), alphaCx and gammaN1 parameters were highly sensitive in the 3-PG model (p < 0.01), while their sensitivity was influenced by stand age and initial density variations. This study confirmed that the parameter-specific optimized 3-PG model could accurately predict the growth process of Chinese fir plantations under different densities. It will provide a scientific reference for regional-scale management of Chinese fir plantations.