文献类型：期刊文献

英文题名：Extending the functionalities of the Biome-BGC model to simulate carbon storage in unmanaged and managed mixed forests

作者：Yan, Ke[1,2] Su, Menglin[1] Li, Haikui[3] Wang, Tongli[2] Lu, Jun[3] Wang, Xiangfu[4] Wang, Weifeng[1]

第一作者：Yan, Ke

通信作者：Wang, WF[1];Wang, TL[2]

机构：[1]Nanjing Forestry Univ, Coll Ecol & Environm, Coinnovat Ctr Sustainable Forestry Southern China, Nanjing 210037, Peoples R China;[2]Univ British Columbia, Dept Forest & Conservat Sci, Vancouver, BC V6T 1Z4, Canada;[3]Chinese Acad Forestry, Inst Forest Resources Informat Tech, Beijing, Peoples R China;[4]Natl Forestry & Grassland Adm, Key Lab Natl Forestry Adm Ecol Hydrol & Disaster P, Northwest Surveying & Planning Inst, Xian 710048, Peoples R China

年份：2025

卷号：237

外文期刊名：COMPUTERS AND ELECTRONICS IN AGRICULTURE

收录：;EI(收录号：20252918807815);Scopus(收录号：2-s2.0-105010841388);WOS:【SCI-EXPANDED(收录号:WOS:001556333800003)】；

基金：This work was supported by the National Key Research and Devel-opment Program of China (No. 2021YFD2200404) , the National Natural Science Foundation of China (No. 32071763) , the China Scholarship Council (No. 202208320373) , and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) . The data were supported by the National Earth System Science Data Center, National Science & Technology Infrastructure of China. (http:// www.geodata.cn) . The Biome-BGC (Version 4.2) software package was provided by the Numerical Terradynamic Simulation Group (NTSG) at the University of Montana.

语种：英文

外文关键词：Improved Biome-BGC; Mixed forests; Carbon storage; Sensitivity analysis

摘要：Ecosystem process-based models have been widely implemented to simulate carbon balance across terrestrial ecosystems at multiple spatial scales. Nevertheless, a notable knowledge gap persists in mechanistically representing carbon dynamics within mixed-species forests, particularly the effects of silvicultural thinning on longterm carbon sequestration. The effects of ecophysiological parameters on carbon dynamics also require further investigation. To address these gaps, we modified the Biome-BGC version 4.2 framework to simulate the carbon dynamics of oak-pine mixed forests in subtropical regions through three key enhancements: 1) developing a novel mixed forest plant functional type, 2) integrating a thinning management module, and 3) optimizing ecophysiological parameters. We tested the improved model on the basis of three independent datasets: 1) forest inventory data, 2) gridded soil organic carbon data, and 3) compiled datasets obtained from the literature. We then applied an extended Fourier amplitude sensitivity test (EFAST) and path analysis to explore the effects of high-sensitivity parameters on carbon storage. Our results demonstrated that the improved model reasonably simulated total carbon storage for both unmanaged and managed oak-pine mixed forests (R2 = 0.50-0.75, mean absolute error = 0.60-1.65 kg C/m2, root mean square error = 0.70-2.10 kg C/m2). The interactions of multiple parameters, such as the annual leaf and fine root turnover fraction, annual whole-plant mortality fraction, and canopy average specific leaf area, had more important effects on carbon storage than variations in a single parameter. Our study advances the mechanistic representation of oak-pine mixed forests while providing a decision-support prediction tool for optimizing carbon storage in the context of global change.