4.7 Article

Revealing the Fingerprint of Climate Change in Interannual NDVI Variability among Biomes in Inner Mongolia, China

期刊

REMOTE SENSING
卷 12, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/rs12081332

关键词

Inner Mongolia; normalized difference vegetation index (NDVI); interannual variability; coefficient of variation

资金

  1. Natural Science Foundation of China [41601580, 41671098, U1904210]
  2. National Key Research and Development Program of China [2017YFD0301106-1, 2018YFC1508900, 2018YFC1508801]
  3. Research Projects of Land and Resources in Henan Province [20190450-7]
  4. Innovative Research Team of Henan Polytechnic University [T2018-4]
  5. Doctor Foundation of Henan University of Technology [B2015-22]

向作者/读者索取更多资源

An understanding of the response of interannual vegetation variations to climate change is critical for the future projection of ecosystem processes and developing effective coping strategies. In this study, the spatial pattern of interannual variability in the growing season normalized difference vegetation index (NDVI) for different biomes and its relationships with climate variables were investigated in Inner Mongolia during 1982-2015 by jointly using linear regression, geographical detector, and geographically weighted regression methodologies. The result showed that the greatest variability of the growing season NDVI occurred in typical steppe and desert steppe, with forest and desert most stable. The interannual variability of NDVI differed monthly among biomes, showing a time gradient of the largest variation from northeast to southwest. NDVI interannual variability was significantly related to that of the corresponding temperature and precipitation for each biome, characterized by an obvious spatial heterogeneity and time lag effect marked in the later period of the growing season. Additionally, the large slope of NDVI variation to temperature for desert implied that desert tended to amplify temperature variations, whereas other biomes displayed a capacity to buffer climate fluctuations. These findings highlight the relationships between vegetation variability and climate variability, which could be used to support the adaptive management of vegetation resources in the context of climate change.

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