Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010

Abstract

Vegetation phenology is a sensitive indicator of the dynamic response of terrestrial ecosystems to climate change. In this study, the spatiotemporal pattern of vegetation dormancy onset date (DOD) and its climate controls over temperate China were examined by analysing the satellite-derived normalized difference vegetation index and concurrent climate data from 1982 to 2010. Results show that preseason (May through October) air temperature is the primary climatic control of the DOD spatial pattern across temperate China, whereas preseason cumulative precipitation is dominantly associated with the DOD spatial pattern in relatively cold regions. Temporally, the average DOD over China's temperate ecosystems has delayed by 0.13 days per year during the past three decades. However, the delay trends are not continuous throughout the 29-year period. The DOD experienced the largest delay during the 1980s, but the delay trend slowed down or even reversed during the 1990s and 2000s. Our results also show that interannual variations in DOD are most significantly related with preseason mean temperature in most ecosystems, except for the desert ecosystem for which the variations in DOD are mainly regulated by preseason cumulative precipitation. Moreover, temperature also determines the spatial pattern of temperature sensitivity of DOD, which became significantly lower as temperature increased. On the other hand, the temperature sensitivity of DOD increases with increasing precipitation, especially in relatively dry areas (e.g. temperate grassland). This finding stresses the importance of hydrological control on the response of autumn phenology to changes in temperature, which must be accounted in current temperature-driven phenological models.

Spatiotemporal Variability in Start and End of Growing Season in China Related to Climate Variability

“…The CCA patterns of EOS and temperature revealed that colder autumn temperatures were linked to earlier EOS in most areas of temperate China. In other words, higher temperature would lead to later EOS, which was consistent with other studies [12,19,65]. In comparison to temperature, preseason precipitation accounted for a smaller proportion of variance in EOS patterns.…”

“…One earlier study indicated that the onset date of dormancy of China's temperate vegetation was delayed in autumn by 3.7 days per decade from 1982 to 1999 [37]. Another study found that the autumn vegetation dormancy onset date over China's temperate ecosystems was delayed by 0.13 days per year from 1982 to 2010 [19]. Therefore, the magnitudes of trends found in previous studies were stronger than our estimate (0.7 days per decade).…”

“…In addition, trend values depended highly on phenophase retrieval methods [18]. In contrast to the Midpoint method applied in this study, Piao et al [37] and Yang et al [19] used polynomial function to reconstruct continuous NDVI series, and then determined the SOS or EOS threshold by the timing of the greatest relative change in multiyear averaged NDVI series. This discrepancy in method selection among different studies caused the difference in phenological trends.…”

Driving force and changing trends of vegetation phenology in the Loess Plateau of China from 2000 to 2010

“…Of these areas, 61.72% positively correlated with temperature and 79.31% positively correlated with precipitation. Yang et al (2014) suggested that the effect of temperature on plant growth will increase if the soil moisture constraints are released, especially in the semiarid areas. This demonstrates that maintaining the appropriate temperature and rainfall in autumn or winter can enhance the photosynthesis of vegetation, extending the growth process (Ciais et al 2005;Griffin et al 2004).…”

“…The main reason for such enhancement of carbon sequestration was found to be the prolonged growing season . But now, more studies have focused on the shift in autumn phenology (Yang et al 2015). Wu et al (2013) found that a significant amount of the interannual variability in the annual net ecosystem productivity can be explained by the changes in the autumn phenology.…”