Phenology shift from 1989 to 2008 on the Tibetan Plateau: an analysis with a process-based soil physical model and remote sensing data

被引:64
作者
Jin, Zhenong [1 ,2 ]
Zhuang, Qianlai [1 ,3 ]
He, Jin-Sheng [4 ,5 ]
Luo, Tianxiang [6 ]
Shi, Yue [4 ]
机构
[1] Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN 47907 USA
[2] Purdue Univ, Interdisciplinary Grad Program, W Lafayette, IN 47907 USA
[3] Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA
[4] Peking Univ, Coll Urban & Environm Sci, Dept Ecol, Beijing 100871, Peoples R China
[5] Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810008, Peoples R China
[6] Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Tibetan Environm Changes & Land Surface P, Beijing 100085, Peoples R China
基金
美国国家科学基金会;
关键词
DELAYED SPRING PHENOLOGY; TERRESTRIAL ECOSYSTEMS; VARIABILITY; WINTER; INDEX; MODIS;
D O I
10.1007/s10584-013-0722-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Phenology is critical to ecosystem carbon quantification, and yet has not been well modeled considering both aboveground and belowground environmental variables. This is especially true for alpine and pan-arctic regions where soil physical conditions play a significant role in determining the timing of phenology. Here we examine how the spatiotemporal pattern of satellite-derived phenology is related to soil physical conditions simulated with a soil physical model on the Tibetan Plateau for the period 1989-2008. Our results show that spatial patterns and temporal trends of phenology are parallel with the corresponding soil physical conditions for different study periods. On average, 1 degrees C increase in soil temperature advances the start of growing season (SOS) by 4.6 to 9.9 days among different vegetation types, and postpones the end of growing season (EOS) by 7.3 to 10.5 days. Soil wetting meditates such trends, especially in areas where warming effect is significant. Soil thermal thresholds for SOS and EOS, defined as the daily mean soil temperatures corresponding to the phenological metrics, are spatially clustered, and are closely correlated with mean seasonal temperatures in Spring and Autumn, respectively. This study highlights the importance and feasibility of incorporating spatially explicit soil temperature and moisture information, instead of air temperature and precipitation, into phenology models so as to improve carbon modeling. The method proposed and empirical relations established between phenology and soil physical conditions for Alpine ecosystems on the Tibetan plateau could also be applicable for other cold regions.
引用
收藏
页码:435 / 449
页数:15
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