Abstract
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.
Highlights
As the most important component of the terrestrial ecosystem, vegetation plays an important role in global hydrologic, energy, and biogeochemical cycles [1,2,3]
Using 34 years of normalized difference vegetation index (NDVI) time series derived from Global Inventory Modeling and Mapping Studies (GIMMS), the main purpose of this study was to address: (1) The spatial patterns of interannual variability of NDVI for different biomes across Inner Mongolia at the growing season and monthly scales; (2) the potential responses of interannual variability of NDVI on climate fluctuation; and (3) the time lag effects of these climate variables
The CVs of the growing season NDVI in our study are about half of those found in another study [6] and about half of the CV values for corresponding steppes in Inner Mongolia as determined by direct measurements of annual aboveground net primary productivity (ANPP) [28]
Summary
As the most important component of the terrestrial ecosystem, vegetation plays an important role in global hydrologic, energy, and biogeochemical cycles [1,2,3]. A comprehensive assessment of climate-related variations in vegetation activity at biome and regional scales is of significance for providing a critical scientific basis of coping with and adaptating to climate change, and has been attracting much attention from the scientific community and the government [6,7]. A great number of studies have explored vegetation dynamics and its responses to climate change at different spatial scales [4,8,9,10]. The NDVI dataset from the Global Inventory Modeling and Mapping Studies (GIMMS), which has been proven to be the longest remotely sensed time series data, could provide unique opportunities for the exploration of long-term vegetation variability [11,20]
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