Global Ecology and Conservation (Oct 2023)
Spatial differentiation characteristics of vegetation greening rates and climate attribution in China's arid and semi-arid regions
Abstract
Since the beginning of the 21st century, vegetation greening in China has continuously increased and ranks among the top globally, especially in the western and northern regions of the country. This study analyzed the characteristics of the greening rates of different vegetation types in China's arid and semi-arid regions in the northwest, using satellite-derived Normalized Difference Vegetation Index (NDVI) data from 2002 to 2021. Furthermore, the study explored the response of greening rates to climate change and its temporal effect. The study found that in the past two decades, the vegetation greening rates in the southeastern region of China's arid and semi-arid areas are higher than that in the northwest. Vegetation change in the arid and semi-arid regions of China exhibits significant spatial heterogeneity in response to climate change. The vegetation greening rates in the southeast of the study area increases with precipitation, while in the northwest, it is promoted by daytime temperature and day-night temperature difference. The greening rates of cultivated vegetation, grassland, and meadow thicket is mainly affected by precipitation, while the greening rates of alpine grassland is mainly affected by day-night temperature difference. In addition, the response of vegetation greening rates to climate in China's arid and semi-arid regions has significant time lag and cumulative effects. Climate changes before the growing season (February to May) can also affect vegetation greening rates during the growing season (June to September). The cumulative climate changes over four months have a greater impact on vegetation greening rate than those over two months. Our study quantified the contribution of climate change to the greening rates of different vegetation types, which can provide references for predicting the dynamic changes of vegetation under future climate change.
