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Warming of the climate system is unequivocal, and the change of climate variables will eventually have a great impact on vegetation cover and agricultural practices, especially in the arid area Xinjiang in China, whose agriculture and ecosystems are heavily vulnerable to climate change. In this paper, normalized difference vegetation index (NDVI) was used to study the vegetation growth and its response to climate change in Xinjiang. Firstly, two NDVI datasets (Global Inventory Modeling and Mapping Studies (GIMMS) and Moderate Resolution Imaging Spectroradiometer (MODIS)) were merged through a pixel-wise regression analysis to obtain a long time series of NDVI data, and then, relationships between yearly NDVI and yearly climate variables, and monthly NDVI and monthly climate variables were extensively investigated for grassland and cropland in northern and southern Xinjiang, respectively. Results show the following: (1) there was an increasing trend in NDVI for both grassland and cropland in both northern and southern Xinjiang over the past decades and trends were significant except that for grassland in northern Xinjiang; (2) precipitation and evaporation were more important than temperature for grassland in northern Xinjiang, while precipitation and temperature were more important than evaporation for grassland in southern Xinjiang and cropland in both northern and southern Xinjiang; (3) NDVI was highly correlated with accumulated monthly precipitation instead of monthly precipitation, and there was a lagged effect of precipitation, temperature, and evaporation on NDVI change. However, lagged effects were only significant in specific months. The results could be helpful to agricultural practices; e.g., based on lagged effect of precipitation, irrigation in July is very important for crop growth. [ABSTRACT FROM AUTHOR]

Understanding the seasonal behaviour of a subtropical forest and its inter-annual variation is crucial to understanding and monitoring its ecosystem function in the context of global warming. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index dataset, a wavelet transform method was used to investigate the inter-annual variations of vegetation phenology in a subtropical mountain and hill region in Fujian, China, during 2001-2010. The results show a distinct inter-annual variation of vegetation phenology related to climate variability even if most areas presented non-significant trends. The start dates significantly advanced and end dates delayed in 2003 and 2008, due to anomalously warm conditions. There was generally a gradient of increasing start dates, and earlier end dates of vegetation growing season, due to colder temperatures at higher altitudes. However, the altitudinal phenology relationship also depends on its corresponding rainfall conditions. Earlier start dates were observed at higher altitudes during rainfall deficit years such as 2008, which coincides with relatively abundant rainfall at higher altitudes. This paper reveals that vegetation phenology was coupled with altitudinal gradient, with distinct responses at different combinations of alternate temperature and precipitation conditions variability. [ABSTRACT FROM AUTHOR]