Abstract
The trend of vegetation phenology dynamics is of crucial importance for understanding vegetation growth and its responses to climate change. However, it remains unclear how the trends of vegetation phenology changed over the past decades. By analyzing phenology data including start (SOS), end (EOS) and length (LOS) of growth season with the Ensemble empirical mode decomposition (EEMD), we revealed the trend evolution of vegetation phenology in China during 1981-2016. Our study suggests that: (1) On the national scale, with EEMD method, the change rates of SOS and LOS were increasing with time, while that of EOS was decreasing. Moreover, the EEMD rates of SOS and LOS exceeded the linear rates in the early-2000s, while that of EOS dropped below the linear rate in the mid-1980s. (2) For each phenological event, the shifted trends took up a large area (~30%), which was close to the sum of all monotonic trends, but more than any monotonic trend type. The shifted trends mainly occurred in the north-eastern China, eastern Qinghai-Tibetan Plateau, eastern Sichuan Basin, North China Plain and Loess Plateau. (3) For each phenological event, the areas in the high-latitude experienced the contrary trends to the other. The amplitude and frequencies of phenology variation in the mid-latitude were stronger than those in the high-latitude and low-latitude. Meanwhile, LOS in the high-latitude was induced by SOS. (4) For each phenological event, the trend evolution varying with longitudes can be divided into eastern region (east of 121°E), central region (92°E–121°E) and western region (west of 92°E) based on the evolution of trends varying with longitudes. The east experienced a delayed SOS and a shorten LOS, which was different from the other areas. The magnitude of delayed trends in EOS and the prolonged trends in LOS were stronger from east to west as longitudes changes. The variation characteristics of LOS with longitude were mainly caused by SOS in the eastern region and by SOS and EOS together in the western and central region. (5) Each land cover types, except Needleleaf Forests, experienced the same trends. For most land cover types, the advance of SOS, delay of EOS and extension of LOS began in the 1980s, the 1990s, and the 1990s, respectively and enhanced several times. Moreover, the magnitudes of Grasslands in SOS and Evergreen Broadleaf Forest in EOS were much greater than the others, while that of croplands was the smallest in each phenological event. Our results showed that the analysis of trend evolution with nonlinear method is very important to accurately reveal the variation characteristics of phenology trends and to extract the inherent trend shifts.
Highlights
Phenology refers to the study of annually or periodically recurring patterns of growth and development of plants and animal behavior [1,2]
Our study showed that over the whole China, the average vegetation phenology derived from EVI2 showed that start of growth season (SOS) has advanced by 0.22 d/yr, end of growth season (EOS) has delayed by 0.20 d/yr and length of growth season (LOS) has lengthened by 0.42 d/yr during 1981–2016 (Figure 2)
In the central region, LOS was controlled by SOS in the beginning and after the early-2000s, LOS became a joint effort of SOS and EOS
Summary
Phenology refers to the study of annually or periodically recurring patterns of growth and development of plants and animal behavior [1,2]. Since the 20th century, especially in the past 20 years, the average surface temperature of the world has risen remarkably, and vegetation phenology has undergone tremendous changes as a response [4] It may make a profound impact on all living creatures as plants are primary ecosystem producers [5]. Though methods like piecewise linear regression models have been proposed to gain trend shifts of phenology [25,26], these methods are sensitive to short-term fluctuations, which makes it hard to identify trend shifts for long time series [27] These methods have a predetermined assumption that the change rates may abruptly alter at the turning points, but do not change with time neither before nor after the turning points. Phenology trends should have gradual temporal variation rather than abrupt change
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