文献类型：期刊文献

英文题名：Integrating forest density and climate factors into forest carbon storage hierarchical growth model system with multi-model compatible: The cases studies for temperate Quercus natural forest and subtropical Cunninghamia plantation in China

作者：Li, Haikui[1] Zhang, Cong[1] Zhao, Jiacheng[2] Wang, Xiaohui[1] Liu, Pengju[1]

第一作者：李海奎

通信作者：Liu, PJ[1]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, State Key Lab Efficient Prod Forest Resources, Key Lab Forest Management & Growth Modelling,Natl, Beijing 100091, Peoples R China;[2]Nanjing Univ Informat Sci & Technol, Sch Ecol & Appl Meteorol, Nanjing 210044, Jiangsu, Peoples R China

年份：2025

卷号：178

外文期刊名：ECOLOGICAL INDICATORS

收录：;EI(收录号：20252818734893);Scopus(收录号：2-s2.0-105009813422);WOS:【SCI-EXPANDED(收录号:WOS:001529986700003)】；

基金：Funding 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：Multi-model compatibility; Parameter classifying; Carbon storage; Climate change; Temperate Quercus natural forest; Subtropical Cunninghamia plantation

摘要：With climate change, the future carbon storage and carbon sequestration potential of forests in China have become a focus for governments, the general public, and scholars. The growth model of forest carbon storage is the most effective and convenient way to predict carbon storage in the future. Here, taking temperate Quercus natural forest and subtropical Cunninghamia plantation in China as examples, we leveraged repeated measurement data in permanent plot from Chinese national forest inventory to develop a hierarchical growth model system that is compatible with multiple theoretical growth equations and conforms to the growth and development laws of forest stands. Forest density and climate factors were integrated into the model and the compatibility of the model prediction was ensured through parameter constraints, formula transformations and simultaneous estimation. Results show that overall, compared with the basic model, the fitting accuracy of the hierarchical model is significantly improved. The R2 of temperate Quercus natural forest and subtropical Cunninghamia plantation reached above 0.96 and 0.94, which increased by about 0.58 and 0.68, and SEE decreased by about 29.1 t & sdot;ha- 1 and 14.4 t & sdot;ha- 1. Climate change has an inhibitory effect on the increase of carbon density and carbon storage in temperate Quercus natural forests in China, and a promoting effect on the increase of carbon density and carbon storage in subtropical Cunninghamia plantations in China. The average variation range of carbon density of temperate Quercus natural forest under the three climate scenarios in the future is -0.1415 t & sdot;ha- 1 to 0.1100 t & sdot;ha- 1, and the carbon storage will decrease by 5.93 x 104 tin 2100. The average variation range of subtropical Cunninghamia plantation is -0.0206 t & sdot;ha- 1 to 0.0258 t & sdot;ha- 1, and the carbon storage will increase by 3.5 x 104 tin 2060. However, the direction of the climatic influence is not consistent in different climate subzones. In the middle temperate eastern region and the south temperate southern and western region, temperature and precipitation are positively correlated with carbon density and carbon storage in Quercus natural forests, while in the temperate western region and the warm temperate northern and eastern region, temperature and precipitation are negatively positively correlated. In the main production areas of Cunninghamia, temperature and precipitation are positively correlated with carbon density and carbon storage in Cunninghamia plantations, while in other areas, temperature and precipitation are negatively correlated. Meanwhile, the classified results of the relationship between forest age and stand carbon density, analogous to site quality grading, indicate that plots with high site quality are more likely to produce large-diameter timber and have a strong positive correlation with stand density. This study proposes a universal, multi-model compatible forest carbon storage hierarchical growth model system that provides methodological guidance and technical support for the dynamic estimation of forest carbon storage under different climate scenarios.