Spatiotemporal variation in vegetation spring phenology and its response to climate change in freshwater marshes of Northeast China

摘要

Understanding wetland vegetation phenology and its response to climate change is important to predict the changes of wetland vegetation in wetland regions. Using the NDVI and climate data, this work studied the spatiotemporal change of start date of vegetation growing season (SOS) and explored the possible effects of climate change on the SOS over freshwater marshes of Northeast China. The results showed that the SOS significantly advanced by 0.52 day per year throughout the freshwater marshes of Northeast China during 2001 to 2016. The significant advancing of SOS was mainly concentrated in freshwater marshes of the Khingan Mountains (the Greater Khingan Mountains and the Lesser Khingan Mountains) and central arid or semi-arid regions (Songnen plain and Liaohe plain) in Northeast China. By contrast, there were weak delay trends of SOS in freshwater marshes of East em Inner Mongolia region, and Sanjiang plain. We found that precipitation was a dominant factor determining the SOS in arid or semi-arid regions (Songnen plain and Liaohe plain), while temperature played a bigger role in determining the SOS in Sanjiang plain and three cold mountains of the Northeast China. During the study period, increasing precipitation in the winter and spring contributed to advancing SOS in Songnen plain and Liaohe plain; the decrease of temperature from December to April explain the delaying SOS in freshwater marshes of Sanjiang Plain; the weak warming of temperature between November and May account for the advancing SOS of freshwater marshes in three cold mountains. In freshwater marshes of cold and the most arid region of Northeast China (Eastern Inner Mongolia), the SOS was influenced by both precipitation and temperature. Decreasing precipitation between January and April, as well as temperature decreases in March and April explain the delay of SOS in freshwater marshes of Eastern Inner Mongolia region. (C) 2019 Elsevier B.V. All rights reserved.