Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982-2013)
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2017 Elsevier B.V. Using NDVI3g vegetation index, we defined 18 phenology metrics to investigate phenological change on the Tibetan Plateau (TP). Considering the heterogeneity of vegetation phenology, we divided TP into 8 vegetation clusters according to a 1:1000000 vegetation cluster map. For regions where phenology is highly sensitive to climate, we investigated the impact of climate variables, such as temperature, precipitation, and solar radiation on phenology using the partial least squares regression (PLS) method. Results indicated (1) that turning points of the starting date of the growing season (SOS) metrics were in 19972000, before which SOS metrics advanced 23d/10a. The ending date of the growing season (EOS) and the length of growing season metrics (LOS) turning points were 2005 and 20042007, respectively. Before the turning points, the EOS metrics had a delayed tendency of 12d/10a, and the LOS metrics also had a prolonging tendency of 12d/10a. After the turning points, the significant levels of SOS and EOS metrics tendency only reached 0.1, and LOS's tendency was insignificant at the 0.1 level. (2) Alpine meadows and alpine shrub meadows changed most intensely on TP. Advanced SOS and delayed EOS were the main reasons of the alpine meadow LOS extension. Advance SOS mainly contributed to the alpine shrub meadow LOS extension. (3) We used meteorological variables, such as temperature, precipitation and solar radiation, to analyze the drastic change of the phenology of alpine meadows and alpine shrub meadows through the PLS method. Temperature was found to be the dominant meteorological variable impacting phenology. In those regions, the previous year autumn and early winter temperature had a positive effect on the SOS phenology. The high temperature in this period would postpone previous year EOS, indirectly delaying SOS in the current year. On the other hand, warming autumn and early winter may slow the fulfilment of chilling requirements and lead to later SOS, which would have a delayed effect on SOS. Except summer, the minimum temperature had a similar effect on vegetation phenology, as average and maximum temperature. Furthermore, the effect of precipitation on phenology fluctuated widely across different months. The previous year autumn and winter precipitation had a negative effect on the SOS phenology, and early spring precipitation had a positive effect. The main factor limiting vegetation development in August was precipitation, and during this month precipitation had a positive impact on the EOS phenology. The influence of solar radiation was mainly during summer and early fall. This study will contribute toward vegetation phenology model improvement.
