Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai–Tibetan Plateau

Abstract

Spring vegetation phenology in temperate and cold regions is widely expected to advance with increasing temperature, and is often used to indicate regional climatic change. The Qinghai–Tibetan Plateau (QTP) has recently experienced intensive warming, but strongly contradictory evidence exists regarding changes in satellite retrievals of spring vegetation phenology. We investigated spatio-temporal variations in green-up date on the QTP from 2000 to 2011, as determined by five methods employing vegetation indices from each of the four sources: three Normalized Difference Vegetation Index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR), Système Pour l’Observation de la Terre (SPOT), MODerate resolution Imaging Spectroradiometer (MODIS), and the Enhanced Vegetation Index (EVI) from MODIS. Results indicate that, at the regional scale, all vegetation indices and processing methods consistently found no significant temporal trend (all P>0.05). This insignificance resulted from substantial spatial heterogeneity of trends in green-up date, with a notably delay in the southwest region, and widespread advancing trend in the other areas, despite a region-wide temperature increase. These changes doubled the altitudinal gradient of green-up date, from 0.63 days 100m−1 in the early 2000s to 1.30 days 100m−1 in the early 2010s. The delays in the southwest region and at high altitudes were likely caused by the decline in spring precipitation, rather than the increasing spring temperature, suggesting that spring precipitation may be an important regulator of spring phenological response to climatic warming over a considerable area of the QTP. Consequently, a delay in spring vegetation phenology in the QTP may not necessarily indicate spring cooling. Furthermore, the phenological changes retrieved from the widely used AVHRR NDVI differed from those retrieved from SPOT and MODIS NDVIs and MODIS EVI, necessitating the use of multiple datasets when monitoring vegetation dynamics from space.