Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012
文献类型：SCI/SSCI论文
| 作者 | Ding M. J.; Li, L. H.; Nie, Y.; Chen, Q.; Zhang, Y. L. |
| 发表日期 | 2016 |
| 关键词 | Spring phenology Spatial pattern Temporal variation Climate change Correlation Tibetan Plateau (TP) growing-season length greater baltic area green-up dates spot ndvi data vegetation phenology satellite data north-america time-series china responses |
| 英文摘要 | The influence of climate change on vegetation phenology is a heated issue in current climate change study. We used GIMMS-3g NDVI data to detect the spatio-temporal dynamics of the start of the growing season (SGS) over the Tibetan Plateau (TP) from 1982 to 2012 and to analyze its relationship with temperature and precipitation. No significant trend was observed in the SGS at the regional scale during the study period (R (2) = 0.03, P = 0.352). However, there were three time periods (1982-1999, 1999-2008 and 2008-2012) with identifiable, distinctly different trends. Regions with a significant advancing trend were mainly scattered throughout the humid and semi-humid areas, whereas the regions with a significant delaying trend were mostly distributed throughout the semi-arid areas. Statistical analysis showed that the response of the SGS to climate change varies spatially. The SGS was significantly correlated with the spring temperature and the start of the thermal growth season (STGS) in the relatively humid area. With increasing aridity, the importance of the spring temperature for the SGS gradually decreased. However, the influences of precipitation and winter temperature on the SGS were complicated across the plateau. |
| 出处 | Journal of Mountain Science |
| 卷 | 13 |
| 期 | 1 |
| 页 | 83-94 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1672-6316 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/43427]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Ding M. J.,Li, L. H.,Nie, Y.,et al. Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012. 2016. |
入库方式： OAI收割
来源：地理科学与资源研究所
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