文献类型：期刊文献

英文题名：Climate Change Effects on Height-Diameter Allometric Relationship Vary with Tree Species and Size for Larch Plantations in Northern and Northeastern China

作者：Xu, Qigang[1,2] Lei, Xiangdong[1,2] Zang, Hao[3] Zeng, Weisheng[4]

第一作者：Xu, Qigang

通信作者：Lei, XD[1];Lei, XD[2]

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]Jiangxi Agr Univ, Coll Forestry, Zhimin Rd 1101, Nanchang 330045, Jiangxi, Peoples R China;[4]State Forestry & Grassland Adm, Acad Forest Inventory & Planning, Beijing 100714, Peoples R China

年份：2022

卷号：13

期号：3

外文期刊名：FORESTS

收录：;EI(收录号：20221411924761);Scopus(收录号：2-s2.0-85127553558);WOS:【SCI-EXPANDED(收录号:WOS:000776998900001)】；

基金：This study was funded by National Natural Science Foundation of China (Grant No. 31870623).

语种：英文

外文关键词：nonlinear mixed-effects model; height-diameter model; climate change; climate-sensitive growth model

摘要：Tree height-diameter relationship is very important in forest investigation, describing forest structure and estimating carbon storage. Climate change may modify the relationship. However, our understanding of the effects of climate change on the height-diameter allometric relationship is still limited at large scales. In this study, we explored how climate change effects on the relationship varied with tree species and size for larch plantations in northern and northeastern China. Based on the repeated measurement data of 535 plots from the 6th to 8th national forest inventory of China, climate-sensitive tree height-diameter models of larch plantations in north and northeast China were developed using two-level nonlinear mixed effect (NLME) method. The final model was used to analyze the height-diameter relationship of different larch species under RCP2.6, RCP 4.5, and RCP8.5 climate change scenarios from 2010 to 2100. The adjusted coefficient of determination R-adj(2), mean absolute error (MAE) and root mean squared error (RMSE) of the NLME models for calibration data were 0.92, 0.76 m and 1.06 m, respectively. The inclusion of climate variables mean annual temperature (MAT) and Hargreaves climatic moisture deficit (CMD) with random effects was able to increase R-adj(2) by 19.5% and reduce the AIC (Akaike's information criterion), MAE and RMSE by a 22.2%, 44.5% and 41.8%, respectively. The climate sensitivity of larch species was ranked as L. gmelinii > the unidentified species group > L. principis > L. kaempferi > L. olgensis under RCP4.5, but L. gmelinii > L. principis > the unidentified species group > L. olgensis > L. kaempferi under RCP2.6 and RCP8.5. Large trees were more sensitive to climate change than small trees.