Driving Forces of the Changes in Vegetation Phenology in the Qinghai–Tibet Plateau

Abstract

Phenological change is an emerging hot topic in ecology and climate change research. Existing phenological studies in the Qinghai–Tibet Plateau (QTP) have focused on overall changes, while ignoring the different characteristics of changes in different regions. Here, we use the Global Inventory Modeling and Mapping Studies (GIMMS3g) normalized difference vegetation index (NDVI) dataset as a basis to discuss the temporal and spatial changes in vegetation phenology in the Qinghai–Tibet Plateau from 1982 to 2015. We also analyze the response mechanisms of pre-season climate factor and vegetation phenology and reveal the driving forces of the changes in vegetation phenology. The results show that: (1) the start of the growing season (SOS) and the length of the growing season (LOS) in the QTP fluctuate greatly year by year; (2) in the study area, the change in pre-season precipitation significantly affects the SOS in the northeast (p < 0.05), while, the delay in the end of the growing season (EOS) in the northeast is determined by pre-season air temperature and precipitation; (3) pre-season precipitation in April or May is the main driving force of the SOS of different vegetation, while air temperature and precipitation in the pre-season jointly affect the EOS of different vegetation. The differences in and the diversity of vegetation types together lead to complex changes in vegetation phenology across different regions within the QTP. Therefore, addressing the characteristics and impacts of changes in vegetation phenology across different regions plays an important role in ecological protection in this region.

Spatiotemporal Characteristics and Heterogeneity of Vegetation Phenology in the Yangtze River Delta

“…Meanwhile, other studies have found a different conclusion in eastern China and Nanjing due to the complexity of the influencing factors [4,12,13]. Methods such as statistical analysis, correlation, and random forests were used to explore the temporal variation characteristics of phenology and response mechanisms [11,[14][15][16][17][18]. In terms of space, the study concluded that spring and autumn phenology in different regions are different with spatial heterogeneity [11,12,14,19].…”

“…Many scholars have analyzed the spatiotemporal characteristics of regional phenology and concluded that spring phenology is advanced and that autumn phenology is delayed [4,9,11]. Meanwhile, other studies have found a different conclusion in eastern China and Nanjing due to the complexity of the influencing factors [4,12,13].…”

“…Methods such as statistical analysis, correlation, and random forests were used to explore the temporal variation characteristics of phenology and response mechanisms [11,[14][15][16][17][18]. In terms of space, the study concluded that spring and autumn phenology in different regions are different with spatial heterogeneity [11,12,14,19]. Although these studies involved the spatial analysis and the conclusion of heterogeneity, little quantitative analysis and discussion of driving factors of heterogeneity has been shown.…”

“…Among the influencing factors, temperature and precipitation have become the main climate factors explaining the interannual variation of phenology. Many studies have shown that there is a significant negative or positive correlation between start or end of vegetation growth season (SOS or EOS) and temperature or precipitation [9,11]. At the same time, the impact of climatic conditions on vegetation phenology has an obvious lag effect [9,23,24].…”

“…Piao [9] pointed out that in the temperate zone of China, the increase in average temperature in spring leads to the advancement of SOS, and the increase of the average temperature in autumn leads to the delay of EOS. There is a significant negative correlation between SOS and average temperature in the 2-3 months before the season [9,11,25]. Relevant scholars have found that feedback between temperature, precipitation and vegetation phenology is at its greatest in the first month preseason [14,26] and directly use the climate factors in first month preseason to conduct phenological related research and obtain better results [11].…”