文献类型：期刊文献

英文题名：Global patterns of allometric model parameters prediction

作者：Wang, Zixuan[1] Huang, Xingzhao[1] Li, Fangbing[1] Chen, Dongsheng[2] Xu, Xiaoniu[1]

第一作者：Wang, Zixuan

通信作者：Huang, XZ[1]

机构：[1]Anhui Agr Univ, Sch Forestry & Landscape Architecture, Hefei 230036, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry, Key Lab Tree Breeding & Cultivat, State Forestry Adm, Beijing 100091, Peoples R China

年份：2023

卷号：13

期号：1

外文期刊名：SCIENTIFIC REPORTS

收录：;Scopus(收录号：2-s2.0-85146928878);WOS:【SCI-EXPANDED(收录号:WOS:000954574000053)】；

基金：AcknowledgementsFinancial support was supported by the Scientific Research Project of Anhui Province (2022AH050873), the Provincial Natural Resources Fund (1908085QC140) and the National Key R&D Program of China (2018YFD1000600).

语种：英文

摘要：Variations in biomass-carbon of forest can substantially impact the prediction of global carbon dynamics. The allometric models currently used to estimate forest biomass face limitations, as model parameters can only be used for the specific species of confirmed sites. Here, we collected allometric models LnW = a + b*Ln(D) (n = 817) and LnW = a + b*Ln((DH)-H-2) (n = 612) worldwide and selected eight variables (e.g., mean annual temperature (MAT), mean annual precipitation (MAP), altitude, aspect, slope, soil organic carbon (SOC), clay, and soil type) to predict parameters a and b using Random Forest. LnW = a + b*Ln(D), drove mainly by climate factors, showed the parameter a range from - 5.16 to - 0.90 [VaR explained (model evaluation index): 66.21%], whereas parameter b ranges from 1.84 to 2.68 (VaR explained: 49.96%). Another model LnW = a + b*Ln((DH)-H-2), drove mainly by terrain factors, showed the parameter a range from - 5.45 to - 1.89 (VaR explained: 69.04%) and parameter b ranges from 0.43 to 1.93 (VaR explained: 69.53%). Furthermore, we captured actual biomass data of 249 sample trees at six sites for predicted parameters validation, showing the R-2 (0.87) for LnW = a + b*Ln(D); R-2 (0.93) for LnW = a + b*Ln((DH)-H-2), indicating a better result from LnW = a + b*Ln((DH)-H-2). Consequently, our results present four global maps of allometric model parameters distribution at 0.5 degrees resolution and provides a framework for the assessment of forest biomass by validation.