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

• Published in: Climatic Change
• Main Authors: Jin, Zhenong, Zhuang, Qianlai, He, Jin-Sheng, Luo, Tianxiang, Shi, Yue, Jin, ZN (reprint author), Purdue Univ, Interdisciplinary Grad Program, W Lafayette, IN 47907 USA.
• Format: Report
• Language: unknown
• Published: 2013
• Subjects: Arctic
• Online Access: http://210.75.249.4/handle/363003/3936; http://210.75.249.4/handle/363003/16709; http://210.75.249.4/handle/363003/21805; http://210.75.249.4/handle/363003/26901; http://210.75.249.4/handle/363003/31997; http://210.75.249.4/handle/363003/37093; https://doi.org/10.1007/s10584-013-0722-7

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. 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 ...