Spatiotemporal variation in alpine grassland phenology in the Qinghai-Tibetan Plateau from 1999 to 2009

Abstract

Plant phenology is the most salient and sensitive indicator of terrestrial ecosystem response to climate change. Studying its change is significantly important in understanding and predicting impressively changes in terrestrial ecosystem. Based on NDVI from SPOT VGT, this paper analyzed the spatiotemporal changes in alpine grassland phenology in Qinghai-Tibetan Plateau from 1999 to 2009. The results are enumerated as follows: (1) The spatial distribution of the average alpine grassland phenology from 1999 to 2009 is closely related to water and heat conditions. Accompanying the deterioration in heat and water conditions from southeast to northwest, the start of growth season (SOG) was delayed gradually, the end of growth season (EOG) advanced slowly, and the length of growth season (LOG) shortened gradually. Elevation played an important role in the regional differentiation of phenology, but a dividing line of approximately 3500 m existed. Below this line, the phenology fluctuated irregularly with altitude change, whereas above the line, the phenology is closely related to altitude change. (2) From 1999 to 2009, SOG of the alpine grassland came earlier by six days per decade (R 2 =0.281, P=0.093), EOG was late by two days per decade (R 2 =0.031, P=0.605), and LOG lengthened by eight days per decade (R 2 =0.479, P=0.018). The early SOG, the late EOG, and the extended LOG mainly occurred at the center and east of the Plateau. SOG in most of the Plateau advanced significantly, especially in the eastern Plateau. (3) The inter-annual phenology changes of the alpine grassland in the Qinghai-Tibetan Plateau exhibited significant differentiation at different elevation and natural zones. The inter-annual changes at high altitude were more complicated than that at low altitude. The most significant phenology changes were found in the eastern Qinghai-Qilian montane steppe zone, and non-significant changes occurred in the Southern Tibet montane shrub-steppe zone. . Plant phenology not only provides a substantial theoretical and practical significance in farming forecast, agricultural and animal-husbandry production guidance, pest indication, seed introduction and selection, and many other aspects but also serves as an important parameter in land process model and global vegetation model [3][4][5][6]. Qinghai-TibetanThis information is very important in promoting people's understanding of the response of vegetation to climate change and improving the simulation accuracy of mass and energy exchanges between the atmosphere and vegetation [7]. As the best indicator in monitoring the influence of climate on vegetation, plant phenology has become the key point of global-change research [8]. Plant phenology analysis based on remote sensing data shows that the growth season of plants in northern hemisphere has lengthened gradually during the last decades [9][10][11][12]. These conclusions are supported by ground observation data. The spring phenophase of most plants in Europe and North America have

Start of vegetation growing season on the Tibetan Plateau inferred from multiple methods based on GIMMS and SPOT NDVI data

“…The HANTS method was employed in the present work to carry out a smoothing treatment of the NDVI data obtained from GIMMS and SPOT-VGT. As a result of the HANTS treatment, two types of data were obtained: one comprised smoothed data having the same temporal resolution as the raw data; the other was the smoothed data with a temporal resolution of 1 day (Ding et al, 2013). Smoothed data were used only in Methods 1, 2 and 3 but not in Method 4.…”

“…One study based on MODIS NDVI data showed that the alpine vegetation SGS advanced in most parts of the TP between 2001 and 2010 (Song et al, 2011). Two of the other studies based on SPOT-VGT NDVI data found an SGS delay between 1998and then an advancement between 2003(Shen, 2011Ding et al, 2013). Zhang et al (2013) have found that the GIMMS NDVI data for 2001-2006 differs substantially from the corresponding SPOT-VGT NDVI data and MODIS NDVI data and they have suggested that the GIMMS NDVI data may suffer from severe data-quality issues in most parts of the western plateau, so they thought that the SGS advanced continuously after the end of the 1990s based on SPOT-VGT NDVI data.…”

“…Overall, studies concerning the trend in the SGS for alpine vegetation on the TP have shown varying results according to the different types of remote sensing data and methods that have been used. However, due to a lack of observed phenological data (Piao et al, 2011;Shen, 2011;Ding et al, 2013), there is as yet no study that has discussed the merits and shortcomings of each remote sensing method with respect to the TP. In this study, we have applied four methods (Threshold of maximum relative change; Threshold of maximum relative change ratio; Threshold of NDVI ratio; and Maximum change of curvature), all of which are currently used in phenological studies on the TP, to investigate the SGS on the TP, using NDVI data from GIMMS and SPOT-VGT.…”

The response of vegetation dynamics of the different alpine grassland types to temperature and precipitation on the Tibetan Plateau

“…Vegetation coverage serves asgrowth of plants (Gurgel and Ferreira 2003). Furthermore, climate change has become a critical point in global change research (Ding et al 2013). Dramatic climate change has been confirmed over the past several decades in several studies (Namgail et al 2012) with an observed increase of 0.6±0.2°C in global mean surface temperature (Zhao et al 2004), leading to more rapid melting of ice, especially in regions of high altitude.…”

“…Moreover, the monthly correlation coefficient for monthly average Normalized Difference Vegetation Index (NDVI) and precipitation is 0.75, which is greater than the correlation coefficient of 0.63 for monthly average NDVI and temperature in the Lhasa area (Chu et al 2007). Previous studies have analyzed NDVI variations and their relationships with temperature and precipitation in the Tibetan Plateau (Chu et al 2007;Xu et al 2011;Ding et al 2013;Wang et al 2015), but correlations between NDVI in different vegetation types and climatic factors have not been observed. In actuality, different vegetation types respond differently to temperature and precipitation.…”