Using phenological and normalized difference vegetation index (NDVI) data from 1982 to 1993 at seven sample stations in temperate eastern China, we calculated the cumulative frequency of leaf unfolding and leaf coloration dates for deciduous species every 5 days throughout the study period. Then, we determined the growing season beginning and end dates by computing times when 50% of the species had undergone leaf unfolding and leaf coloration for each station year. Next, we used these beginning and end dates of the growing season as time markers to determine corresponding threshold NDVI values on NDVI curves for the pixels overlaying phenological stations. Based on a cluster analysis, we determined extrapolation areas for each phenological station in every year, and then implemented the spatial extrapolation of growing season parameters from the seven sample stations to all possible meteorological stations in the study area.Results show that spatial patterns of growing season beginning and end dates correlate significantly with spatial patterns of mean air temperatures in spring and autumn, respectively. Contrasting with results from similar studies in Europe and North America, our study suggests that there is a significant delay in leaf coloration dates, along with a less pronounced advance of leaf unfolding dates in different latitudinal zones and the whole area from 1982 to 1993. The growing season has been extended by 1.4-3.6 days per year in the northern zones and by 1.4 days per year across the entire study area on average. The apparent delay in growing season end dates is associated with regional cooling from late spring to summer, while the insignificant advancement in beginning dates corresponds to inconsistent temperature trend changes from late winter to spring. On an interannual basis, growing season beginning and end dates correlate negatively with mean air temperatures from

Understanding vegetation responses to climate change on the Tibetan Plateau (TP) helps in elucidating the land-atmosphere energy exchange, which affects air mass movement over and around the TP. Although the TP is one of the world's most sensitive regions in terms of climatic warming, little is known about how the vegetation responds. Here, we focus on how spring phenology and summertime greenness respond to the asymmetric warming, that is, stronger warming during nighttime than during daytime. Using both in situ and satellite observations, we found that vegetation green-up date showed a stronger negative partial correlation with daily minimum temperature (Tmin ) than with maximum temperature (Tmax ) before the growing season ('preseason' henceforth). Summer vegetation greenness was strongly positively correlated with summer Tmin , but negatively with Tmax . A 1-K increase in preseason Tmin advanced green-up date by 4 days (P < 0.05) and in summer enhanced greenness by 3.6% relative to the mean greenness during 2000-2004 (P < 0.01). In contrast, increases in preseason Tmax did not advance green-up date (P > 0.10) and higher summer Tmax even reduced greenness by 2.6% K(-1) (P < 0.05). The stimulating effects of increasing Tmin were likely caused by reduced low temperature constraints, and the apparent negative effects of higher Tmax on greenness were probably due to the accompanying decline in water availability. The dominant enhancing effect of nighttime warming indicates that climatic warming will probably have stronger impact on TP ecosystems than on apparently similar Arctic ecosystems where vegetation is controlled mainly by Tmax . Our results are crucial for future improvements of dynamic vegetation models embedded in the Earth System Models which are being used to describe the behavior of the Asian monsoon. The results are significant because the state of the vegetation on the TP plays an important role in steering the monsoon.

Rapid temperature increase and its impacts on alpine ecosystems in the Qinghai-Tibetan Plateau, the world's highest and largest plateau, are a matter of global concern. Satellite observations have revealed distinctly different trend changes and contradicting temperature responses of vegetation green-up dates, leading to broad debate about the Plateau's spring phenology and its climatic attribution. Large uncertainties in remote-sensing estimates of phenology significantly limit efforts to predict the impacts of climate change on vegetation growth and carbon balance in the Qinghai-Tibetan Plateau, which are further exacerbated by a lack of detailed ground observation calibration. Here, we revealed the spatiotemporal variations and climate drivers of ground-based herbaceous plant green-up dates using 72 green-up datasets for 22 herbaceous plant species at 23 phenological stations, and corresponding daily mean air temperature and daily precipitation data from 19 climate stations across eastern and southern parts of the Qinghai-Tibetan Plateau from 1981 to 2011. Results show that neither the continuously advancing trend from 1982 to 2011, nor a turning point in the mid to late 1990s as reported by remote-sensing studies can be verified by most of the green-up time series, and no robust evidence for a warmer winter-induced later green-up dates can be detected. Thus, chilling requirements may not be an important driver influencing green-up responses to spring warming. Moreover, temperature-only control of green-up dates appears mainly at stations with relatively scarce preseason snowfall and lower elevation, while coupled temperature and precipitation controls of green-up dates occur mostly at stations with relatively abundant preseason snowfall and higher elevation. The diversified interactions between snowfall and temperature during late winter to early spring likely determine the spatiotemporal variations of green-up dates. Therefore, prediction of vegetation growth and carbon balance responses to global climate change on the world's roof should integrate both temperature and snowfall variations.

Phenology studies the cycle of events in nature that are initiated and driven by an annually recurring environment. Plant phenology is expected to be one of the most sensitive and easily observable natural indicators of climate change. On the Tibetan Plateau (TP), an accelerated warming since the mid-1980s has resulted in significant environmental changes. These new conditions are accompanied by phenological changes that are characterized by considerable spatiotemporal heterogeneity. Satellite remote sensing observed widespread advance in the start of the plant growing season across the plateau during the 1980s and 1990s but substantial delay over 2000–2011 in the southwest although it continued to advance in the northeast regions of the TP. Both observational studies and controlled experiments have revealed, to some extent, the positive role of higher preseason temperature and even more precipitation in advancing the leaf onset and first flowering date of the TP. However, a number of rarely visited research issues that are essential for understanding the role of phenology in ecosystem responses and feedback processes to climate change remain to be solved. Our review recommends that addressing the following questions should be a high priority. How did other phenological events change, such as flowering and fruiting phenology? What are the influences from environmental changes other than temperature and precipitation, including human activities such as grazing? What are the genetic and physiological bases of plants phenological responses? How does phenological change influence ecosystem structure and function at different scales and feedback to the climate system? Investigating these research questions requires, first of all, new data of the associated environmental variables, and consistent and reliable phenological observation using different methodologies (i.e. in situ observations and remote sensing).

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