Evaluation of Multiple Spring Phenological Indicators of Yearly GPP and NEP at Three Canadian Forest Sites
作者:Wang, Q (Wang, Qian)[ 1,2 ] ; Zhang, LF (Zhang, Lifu)[ 1 ] ; Wu, TX (Wu, Taixia)[ 1 ] ; Cen, Y (Cen, Yi)[ 1 ] ; Huang, CP (Huang, Changping)[ 1 ] ; Tong, QX (Tong, Qingxi)[ 1 ]
REMOTE SENSING
卷: 6  期: 3  页: 1991-2007
DOI: 10.3390/rs6031991
出版年: MAR 2014

摘要
Phenological shifts in events such as flowering and bud break are important indicators of ecosystem processes, and are therefore of particular significance for carbon (C) cycle research. Using long-term flux data from three contrasting plant functional type (evergreen and deciduous) boreal forest sites, we evaluated and compared the responses of annual C fluxes to multiple spring phenological indicators, including the C-uptake period onset (CUP onset), spring temperature (average value from March to May), and satellite-derived enhanced vegetation index (EVI) (average value from March to May). We found that the CUP onset was negatively correlated with annual gross primary production (GPP) for all three sites, but that its predictive strength for annual net ecosystem production (NEP) differed substantially among plant functional types. Spring temperature demonstrated particularly good potential for predicting both annual GPP and NEP for the evergreen sites, but not for the deciduous site. Spring EVI was demonstrated to have potential for predicting annual NEP for all sites. However, both plant functional types confounded the correlation of annual NEP with annual GPP. Although none of these phenological indicators provided consistent insight into annual C fluxes, using various currently available datasets our results remain potentially useful for the assessment of forest C cycling with future climate change. Previous analyses using only a single phenological metric should be considered with caution.

通讯作者地址: Zhang, LF (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China