Abstract
Climate change has significantly affected the ecosystem of the Tibetan Plateau. There, temperature rises and altered precipitation patterns have led to notable changes in its vegetation growth processes and vegetation cover features. Yet current research still pays relatively little attention to the regional climatic determinants and response patterns of such vegetation dynamics. In this study, spatial patterns in the response of the normalized difference vegetation index (NDVI) to climate change and its dynamic characteristics during the growing season were examined for the Tibetan Plateau, by using a pixel-scale-based geographically weighted regression (GWR) based on the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data, as well as data for temperature and moisture indices collected at meteorological stations, for the period 1982–2015. The results show the following. Spatial nonstationary relationships, primarily positive, were found between the NDVI and climatic factors in the Tibetan Plateau. However, warming adversely affected vegetation growth and cover in some arid and semiarid regions of the northeast and west Tibetan Plateau. Additionally, precipitation played a dominant role in the NDVI of the Tibetan Plateau in the largest area (accounting for 39.7% of total area). This suggests that increased moisture conditions considerably facilitated vegetation growth and cover in these regions during the study period. Temperature mainly played a dominant role in the NDVI in some parts of the plateau sub-cold zone and some southeastern regions of the Tibetan Plateau. In particular, the minimum temperature was the dominant driver of NDVI over a larger area than any of the other temperature indices. Furthermore, spatial regressions between NDVI dynamics and climatic variability revealed that a faster warming rate in the arid and semiarid regions impeded vegetation growth through mechanisms such as drought intensification. Moisture variability was found to act as a key factor regulating the extent of vegetation cover on the south Tibetan Plateau.
Highlights
To climate change and its dynamic characteristics during the growing season were examined for the Tibetan Plateau, by using a pixel-scale-based geographically weighted regression (GWR) based on the Global Inventory Modeling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) data, as well as data for temperature and moisture indices collected at meteorological stations, for the period 1982–2015
The GWR coefficients of the mean and variability of each climatic factor were subjected to a spatial autocorrelation analysis, to determine whether their relationships of NDVI and its dynamics to climate change are spatially stationary (Table 2)
Spatial nonstationary relationships were simulated between the NDVI
Summary
Hydrothermal conditions in the climatic environment are the primary nonbiological factors that determine vegetation characteristics (e.g., phenology, productivity, and distribution patterns of plants) and their dynamic variation [1,2]. The normalized difference vegetation index (NDVI) is a commonly used index to study vegetation growth and cover, and it has been extensively applied on various regional scales [3,4]. Time-series NDVI data are often used to analyze the characteristics of changes in vegetation and their relationships with climatic factors [5]. While able to promote vegetation growth and development as well as the physiological and biochemical attributes of vegetation, changes in climatic conditions may adversely affect vegetation growth and cover and display a Remote Sens.
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