# The Response of Vegetation Dynamics to Climate in Xinjiang from 1991 to 2018
## 1 Introduction  
Vegetation, as a vital component of biodiversity and ecosystems on the Earth, plays a crucial role in water conservation, soil water retention, windbreak, and sand fixation, as well as biodiversity protection [1; 2; 3; 4]. Climate significantly influences vegetation growth, particularly in terms of precipitation and temperature [5; 6; 7; 8; 9]. Firstly, increasing temperatures may advance and prolong the growth season of the region [10], which contributes to biomass accumulation. More humid environments will promote photosynthesis and the growth of vegetation [11]. Under the context of global warming, vegetation has become increasingly sensitive to climate change. In addition, human activities exert both positive and negative impacts on vegetation [12; 13]. Under the combined influence of both factors, once the vegetation in a region is damaged, it not only loses ability to regulate the local climate and maintain ecological balance but may also lead to desertification, becoming a source of dust storms. Therefore, in the context of climate change, analyzing the spatiotemporal characteristics of vegetation and understanding its response mechanisms to both climate change and human activities are crucial for providing a scientific basis for vegetation protection and restoration and essential for assessing the ecological health of vegetation. In recent years, vegetation dynamics monitoring has primarily relied on remote sensing techniques. Typical indicators of plant growth include the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Gross Primary Productivity (GPP) [12; 14; 15; 16]. Many researchers have utilized long-term remote sensing data to thoroughly examine the spatial and temporal patterns of these indicators, exploring the underlying driving mechanisms. Analytical techniques such as residual analysis, Pearson correlation, Theil-Sen trend analysis, and Mann-Kendall tests have been commonly applied [17; 18; 19; 20]. [PERSON] et al. [21], for instance, demonstrated that the partial correlation coefficient (RNDVI-GT) between the year-to-year variability of NDVI during the growing season and temperature in regions above 30\({}^{\circ}\) N latitude notably decreased between 1982 and 2011. Similarly, [PERSON] et al. [22] determined that from 2000 to 2016, 45.78% of NDVI changes in China's Loess Plateau were attributed to climate change, with the effect of climate on NDVI becoming more pronounced over longer timescales. Using the Empirical Orthogonal Function (EOF) method, [PERSON] et al. [23] analyzed vegetation changes in Xinjiang from 1982 to 2021, identifying five climatic factors, including temperature and precipitation, that positively influenced vegetation growth. Research by [PERSON] et al. [24] simulated GPP and indicated that rising temperatures and lower precipitation contributed to decreased GPP across much of the southwestern northern United States due to water stress. Collectively, these findings emphasize that climate, particularly temperature and precipitation, plays a critical role in influencing the growth and distribution of vegetation. Diverse regional features lead to pronounced spatial and temporal variations in how different vegetation types respond to climate factors [25; 26; 27; 28]. For instance, in arid and semi-arid zones, various plant types, from desert shrubs to mountain forests, illustrate the differing impacts of climate on vegetation, which is essential for understanding ecosystem responses to climate change. Furthermore, ecosystems show marked sensitivity to climate fluctuations, especially regarding temperature and precipitation, making these areas ideal for studying how climate change influences vegetation dynamics. This context underscores the importance of grasping vegetation responses within specific environmental setting. Xinjiang is located in the northwest region of China, with significant climate differences between the north and south and a fragile ecosystem.