文献类型：期刊文献

英文题名：CLIMATIC SIGNALS IN WOOD PROPERTY VARIABLES OF PICEA CRASSIFOLIA

作者：Lu, Jianxiong[1,2] Xu, Jinmei[2] Wu, Yiqiang[] Li, Xianjun[1] Evans, Robert[3] Downes, Geoffrey M.[4,5]

第一作者：吕建雄;Lu, Jianxiong

通信作者：Lu, JX[1]

机构：[1]Cent South Univ Forestry & Technol, Coll Mat Sci & Engn, Changsha, Hunan, Peoples R China;[2]Chinese Acad Forestry, Res Inst Wood Ind, State Key Lab Tree Genet & Breeding, Beijing 100091, Peoples R China;[3]CSIRO Mat Sci & Engn, Clayton, Vic 3169, Australia;[4]CSIRO Ecosyst Sci, Hobart, Tas 7001, Australia;[5]CRC Forestry, Hobart, Tas 7001, Australia

年份：2015

卷号：47

期号：2

起止页码：131-140

外文期刊名：WOOD AND FIBER SCIENCE

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000353668400001)】；

基金：This work was funded by the National Natural Science Foundation of China (No. 31300478) and Special Fund of Chinese Academy of Forestry for Fundamental Research (CAFYBB2014QB010). The Academy of Water Resource Conservation Forest of Qilian Mountains in Gansu provided appreciable support for fieldwork. Thanks to Winston Liew in CSIRO for technical assistance with sample preparation and measurement.

语种：英文

外文关键词：Wood property; cell characteristics; microfibril angle; wood density; treering; dendroclimatology

摘要：Little attention has been given to climatic signals in wood properties. In this study, ring width (RW), annual average microfibril angle (MFA), annual average tracheid radial diameter (TRD), and annual average density (DEN), as the annual and intra-annual wood property variables, were measured at high resolution by SilviScan-3 on dated Picea crassifolia trees. Dendroclimatological methods were used to analyze climatic signals registered in wood property variables. RW, MFA, and TRD negatively correlated with temperature and positively correlated with precipitation in the growing season, whereas the reverse was true for DEN. Climatic signals recorded in the earlywood were similar to those measured for the full width of the annual rings. Climatic signals recorded in latewood were very weak except for latewood MFA. This study showed that wood property variables could be extensive resources for learning more about the influences of climate on tree growth and how trees adapt to ongoing climate change.