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Ying Yong Sheng Tai Xue Bao. 2016 Sep;27(9):2797-2806. doi: 10.13287/j.1001-9332.201609.003.

[Spatiotemporal variation of vegetation phenology in the Daxing'an Mountains stratified by eco-geographical regions.]

[Article in Chinese; Abstract available in Chinese from the publisher]

Author information

1
School of Geographical Sciences, Northeast Normal University, Changchun 130024, China.

Abstract

in English, Chinese

Vegetation phenology is a good indicator of climate change, because of the close correlation between vegetation and climate. The Daxing'an Mountains, located in Chinese northernmost region, are more sensitive to climate change. Researching the spatio-temporal variation of vegetation phenology in this region is of great significance for assessing the influence of global change on terrestrial ecosystem. According to the eco-geographical zoning of China, the Daxing'an Mountains can be divided into for four eco-geographical regions. In this study, the spatial distribution and dynamics of vegetation phenology in the Daxing'an Mountains were analyzed using 8-km resolution GIMMS NDVI 3g dataset from 1982 to 2012. Results showed that the start of growing season in all partitions exhibited an advancing trend, and the end of growing season in all partitions had an extending trend. Vegetation phenology which was sensitive to the change of meteorological factors had a stronger correlation with temperature than with precipitation for all four eco-geographical regions. There was a significant negative correlation between the start of growing season in the northern region and spring temperature. Except for the south of the Daxing'an Mountains, the ending days of growing season in the other three eco-geographical regions had significant negative correlations with summer precipitation. The change of vegetation phenology in the whole study was obvious along with altitude and latitude.

KEYWORDS:

Daxing'an Mountains; GIMMS NDVI 3g; eco-geographical region; vegetation phenology

PMID:
29732841
DOI:
10.13287/j.1001-9332.201609.003
[Indexed for MEDLINE]

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