## 1 Introduction  
Global warming has significantly increased the frequency and intensity of extreme climatic events, placing ecosystems under unprecedented pressure [1]. In recent years,the complex impacts of extreme climate events on ecosystems have attracted increasing attention. Single extreme climate events (e.g., droughs and heat waves occurring independently) have been shown to have very disruptive effects on ecosystems [2;3]. These events have been demonstrated to have short-term impacts on the carbon cycle and hydrological processes, and to be capable of permanently altering ecosystem functioning [2]. Furthermore, [PERSON] et al. [4] underscored the long-term threats to biodiversity and forest health posed by single events. As climate change intensifies, single extreme events are evolving into compound events (e.g., droughs superimposed on heat waves), and the impacts on ecosystems are becoming more complex and far-reaching [5;6]. There is an urgent need for an in-depth exploration of the dynamic mechanisms of compound events and their impact on ecosystems. Both singular and compound extreme climate events have severe impacts on ecosystems [7]; however, the long-term ecological responses to these events remain poorly understood. In arid regions of the Northern Hemisphere, extreme high temperatures and drought have reduced forest growth and heightened wildfire risks [8;9]. Conversely, in some high-latitude areas, such events occasionally enhanced vegetation productivity by extending the growing season and improving carbon assimilation efficiency [2;10]. This variability underscores the need to comprehensively understand how ecosystems respond to extreme climate indices (ECIs), which is essential for disaster preparation and the development of effective ecosystem protection strategies, especially in vulnerable regions. Extreme climate events are often quantified using specific indices. The Expert Team on Climate Change Detection and Indices (ETCCDI) has developed a widely accepted set of indices that are frequently applied in global studies [11;12]. These indices include 16 measures of extreme temperature and 10 measures of extreme precipitation. As extreme climate events become more frequent, compound extreme climate events are intensifying [13]. These compound indices typically combine two or more variables--such as temperature, precipitation, hurricanes, or floods--and are quantified using methods like the Copula function [14;15] or joint probability density functions [16;17]. These methods are particularly effective for modeling the climate anomalies observed in hydrometeorology [18]. The application of the Copula theory [19] allows for the modeling of the correlation between temperature and precipitation, providing a powerful tool for capturing compound extreme events. Such events have profound impacts on both ecosystems and human health [5], although the mechanisms and temporal patterns governing their occurrence remain unclear. We hypothesize that the effects of extreme climatic events on ecosystems will not only result in immediate and intense impacts but may also exhibit temporal dynamics in the long term, shaped by the geographic and climatic diversity of the regions. This study focuses on three core aspects: First, it examines the influence of ECIs on two key ecological indicators (EIs)--the NDVI and GPP--which reflect different dimensions of ecosystem health. The NDVI primarily measures the structure and greenness of vegetation, while the GPP represents the capacity for carbon assimilation and photosynthesis. The selection of these two indicators allows for the simultaneous evaluation of vegetation cover, growth, productivity, and material cycling. The analysis investigates how these indicators, despite their functional differences, exhibit varying responses across different altitudes and geographical topographies. Second, the study assesses the temporal stability of these impacts over time. Third, it explores the differences in ecosystem sensitivity and resilience between higher and lower altitudes.