Abstract
Satellite-derived vegetation phenophases are frequently used to study the response of ecosystems to climate change. However, limited studies have identified the common phenological variability across different climate and vegetation zones. Using NOAA/Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) dataset, we estimated start of growing season (SOS) and end of growing season (EOS) for Chinese vegetation during the period 1982–2012 based on the Midpoint method. Subsequently, the empirical orthogonal function (EOF) analysis was applied to extract the main patterns of phenophases and their annual variability. The impact of climate parameters such as temperature and precipitation on phenophases was investigated using canonical correlation analysis (CCA). The first EOF mode of phenophases exhibited widespread earlier or later SOS and EOS signals for almost the whole country. The attendant time coefficients revealed an earlier SOS between 1996 and 2008, but a later SOS in 1982–1995 and 2009–2012. Regarding EOS, it was clearly happening later in recent years, mainly after 1993. The preseason temperature contributed to such spatiotemporal phenological change significantly. The first pair of CCA patterns for phenology and preseason temperature was found to be similar and its time coefficients were highly correlated to each other (correlation coefficient >0.7). These results indicate that there is a substantial amount of common variance in SOS and EOS across different vegetation types that is related to large-scale modes of climate variability.
Highlights
Because plants are equipped with a phenotypic plasticity, they can grow and develop in changing environmental conditions as long as the conditions do not alter beyond the tolerances of the species [1]
We employed the empirical orthogonal function (EOF) analysis to assess the variability of satellite-derived growing season during the period of 1982 ́2012
The results showed that the first EOF mode was dominated by a relatively homogeneous structure, i.e. an earlier or later start of season (SOS) and end of season (EOS) for almost the whole country
Summary
Because plants are equipped with a phenotypic plasticity, they can grow and develop in changing environmental conditions as long as the conditions do not alter beyond the tolerances of the species [1]. Among various types of phenotypic plasticity (e.g., morphological, physiological, behavioral, phenological), phenology is sensitive to small variations in environmental factors [2]. Regarding phenophases of plant senescence, the overall trend is towards later phenophases mainly due to the remarkable autumn warming, but the trends were less apparent and exhibited distinct regional difference [6]. Plant phenology responds to climate change, and controls many feedbacks of vegetation to the climate system [7,8]. The change in plant phenology can change surface roughness length and albedo, further impacting sensible and latent heat flux as well as water flux from surface to Remote Sens. The change in plant phenology can change surface roughness length and albedo, further impacting sensible and latent heat flux as well as water flux from surface to Remote Sens. 2016, 8, 433; doi:10.3390/rs8050433 www.mdpi.com/journal/remotesensing
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