文献类型：期刊文献

英文题名：Empirical analysis of the influences of meteorological factors on the interannual variations in carbon fluxes of a Quercus variabilis plantation

作者：Zhou, Yu[1,2,3] Zhang, Jinsong[1,2,3] Yin, Changjun[1,2,3] Huang, Hui[1,2,3] Sun, Shoujia[1,2,3] Meng, Ping[1,2,3]

第一作者：Zhou, Yu;周晔

通信作者：Zhang, JS[1];Yin, CJ[1];Zhang, JS[2];Yin, CJ[2];Zhang, JS[3];Yin, CJ[3]

机构：[1]Chinese Acad Forestry, Res Inst Forestry, Key Lab Tree Breeding & Cultivat, Natl Forestry & Grassland Adm, Beijing 100091, Peoples R China;[2]Nanjing Forestry Univ, Collaborat Innovat Ctr Sustainable Forestry Southe, Nanjing 210037, Peoples R China;[3]Henan Xiaolangdi Earth Crit Zone Natl Res Stn Midd, Jiyuan 454650, Peoples R China

年份：2022

卷号：326

外文期刊名：AGRICULTURAL AND FOREST METEOROLOGY

收录：;Scopus(收录号：2-s2.0-85138999851);WOS:【SCI-EXPANDED(收录号:WOS:000868300200001)】；

基金：This research was supported by the National Nonprofit Institute Research Grant of the Chinese Academy of Forestry (CAFYBB2018ZA001, CAFYBB2017ZX002) and the Project of the Collaborative Innovation Center for Sustainable Forestry in Southern China of Nanjing Forestry University. Some meteorological data were provided by the Chinese National Meteorological Information Center. We greatly appreciate the three anonymous reviewers for their insightful and constructive comments that helped us to improve our manuscript.

语种：英文

外文关键词：Carbon flux; Accumulated temperature; Eddy covariance; Structural equation modeling; Plantation ecosystem

摘要：Influences of meteorological factors on the carbon fluxes of a forest ecosystem can vary with time scales. While many studies were made on daily to annual variations of measured carbon flux of forest ecosystems, few were conducted on the variations of observed carbon fluxes over longer (decadal or more) time scale. This study quantified the influences of meteorological variables on the measured carbon fluxes in a Quercus variabilis plantation from 2006 to 2021 using principal component analysis (PCA) and cluster analysis (CA). PCA was used to identify the most important meteorological variables. They are monthly mean daily maximum global radiation (Rg), monthly effective accumulated temperature (Tac), monthly mean daily maximum vapor pressure deficit (VPD), and monthly precipitation (PP). CA was used to group 192 observed months into four groups based on those four meteorological variables and their effects on the observed carbon fluxes. Structural equation modeling (SEM) was then used to quantify the relative importance and direct or indirect effects of those four meteoro-logical factors on carbon fluxes at the interannual timescale in each of the four groups. The results showed that air temperature had dominant influence on net ecosystem productivity (NEP) and ecosystem respiration (Re) with its relative importance measured by standardized coefficients (SC) of 0.59 and 0.97, respectively. PP directly impacted gross primary production (GPP) with an SC of 0.40 and indirectly influenced NEP and Re. The importance of a given meteorological factor on carbon fluxes and the dominant meteorological factors varied among the four groups. Tac mainly influenced Re with a SC of 0.79 in Group 1 (the nongrowing season). The direct effects of PP on NEP and GPP and indirect effects on Re were most prominent in Group 2 (the transition stage between the nongrowing season and the growing season). Tac and PP had greater influences than other two variables in Group 3 (the transitional stage of early growth and vigorous growth and the transitional stage of steady growth and dormant period). NEP increased with Tac, while excessive rainy weather accompanied by a decrease in temperature and radiation reduced Re and GPP in Group 4 (the wet season). The short-term seasonal droughts with warm air temperatures but little precipitation (mainly in June) led to significant reductions in both GPP and NEP of the Quercus variabilis plantation ecosystem in the warm-temperate continental monsoon climate zone. Our results can be used to guide managing forest plantations in temperate region in China to maximize their carbon sequestration.