Prominent vegetation greening in spring and autumn across China during the 1981–2018 period

Abstract

Vegetation greening in China has been extensively examined, but little is known about its seasonal characteristics and its association with soil moisture (SM) and temperature changes. Using high-resolution (0.1°, 8 d) datasets of leaf area index (LAI), together with SM, soil temperature (ST) datasets, and the dominance analysis method, this study is designed to detect seasonal vegetation changes across China during 1981–2018 and its links to climate change. The results show that 56.8% of land area across China experienced a greening trend while 6.6% browning trend through 1981–2018. LAI increasing area expanded to a maximum of 59.3% in spring and the decreasing area reached a maximum of 10.6% in autumn. Spring increases in LAI in main vegetation regions were significantly correlated with positive ST anomalies, while autumn decreases in LAI except sparsely vegetated regions were correlated with negative SM anomalies. Combined SM and temperature anomalies explain 10.9% of the observed LAI changes, which is 4 times larger than that directly explained by precipitation and surface air temperature (2.7%). The warming of soil under climate change was driving the LAI increases, while drying was largely responsible for LAI decreases. These findings provide further evidence of climate change impacts on regional ecosystems and highlight the importance of soil heat and water conditions in translating global warming signals.

Keywords

• vegetation greening
• vegetation browning
• soil moisture
• soil temperature
• climate change