Vegetation response to climate zone dynamics and its impacts on surface soil water content and albedo in China

Extensive research has focused on the response of vegetation to climate change, including potential mechanisms and resulting impacts. Although many studies have explored the relationship between vegetation and climate change in China, research on spatiotemporal distribution changes of climate regimes using natural vegetation as an indicator is still lacking. Further, limited information is available on the response of vegetation to shifts in China's regional climatic zones. In this study, we applied Mann-Kendall, and correlation analysis to examine the variabilities in temperature, precipitation, surface soil water, normalised difference vegetation index (NDVI), and albedo in China from 1982 to 2012. Our results indicate significant shifts in the distribution of Koppen-Geiger climate classes in China from 12.08% to 18.98% between 1983 and 2012 at a significance level of 0.05 (MK). The percentage areas in the arid and continental zones expanded at a rate of 0.004%/y and 0.12%/y, respectively, while the percentage area in the temperate and alpine zones decreased by -0.05%/y and - 0.07%/y. Sensitivity fitting results between simulated and observed changes identified temperature to be a dominant control on the dynamics of temperate (r(2)= 0.98) and alpine (r(2)= 0.968) zones, while precipitation was the dominant control on the changes of arid (r(2) = 0.856) and continental (r(2) = 0.815) zones. The response of the NDVI to albedo infers a more pronounced radiative response in temperate (r = -0.82, p <.01) and alpine (r = -0.476, p <.05) compared to arid and continental zones. Furthermore, we identified more pronounced monthly increasing trends in NDVI and soil water, corresponding to weak changes in albedo during vegetation growing periods. Our results suggest that climate zone shifting has considerable impacts on the vegetation in China andwill have larger ecological impacts through radiative or non-radiative feedback mechanisms in future warming scenarios. (C) 2020 Elsevier B.V. All rights reserved.