###### Abstract  
Ecological quality in China has experienced significant improvements due to the interplay of climate change and human activities. Nevertheless, previous studies exploring the trend of ecological parameters have always overlooked the effects of land use types. Therefore, in this study, we explored the spatiotemporal variation in ecological parameters in various land use types and discussed the relationship between ecological parameters and climatic factors in China during the first 20 years of the 21 st century. The results show that: (1) The area of grassland and unutilized land decreased, and the area of other land use types increased. (2) Distinct variations in the average, slope, and interval distribution of ecological parameters across various land use types were evident. Particularly significant increases in ecological parameters were observed in cultivated land and forest. (3) The influence of land use and land cover change on ecological parameters was evident. The conversion of cultivated land, forest, and grassland into water bodies, constructive land, and unutilized land resulted in a significant decrease in ecological parameters. (4) The distinct climatic conditions resulted in heightened monthly variations in the ecological parameters. Significant monthly fluctuations in ecological parameters were observed for cultivated land, forest, grassland, and constructed land, while water bodies and unutilized land did not exhibit such variations. (5) The correlation between ecological parameters and climatic factors varied considerably in various land use types in different regions. land use and land cover change; ecological parameters; China 2024 13 572 12 202  
In the context of climate change, vegetation exhibits distinct seasonal and interannual variations [17; 18], playing a crucial role in climate regulation through its impact on factors such as evapotranspiration, surface albedo, and surface roughness. Additionally, vegetation significantly contributes to soil and water conservation and ecological enhancement [18]. The evaluation of vegetation ecosystem quality is commonly employed to assess the growth status of vegetation in specific areas [19]. The most recent ecological environment standard, HJ1172-2021 [20], released by the Ministry of Ecology and Environment of the People's Republic of China in May 2021, outlines the technical guidelines for the National Ecological Condition Survey and Assessment, particularly focusing on Ecosystem Quality Assessment. This assessment primarily considers parameters such as vegetation coverage (VC), leaf area index (LAI), and gross primary productivity (GPP). VC is utilized to describe the horizontal structural state of vegetation [21; 22], while LAI indicates the vertical structural complexity of vegetation [23; 24], and GPP reflects the photosynthetic capacity of vegetation [25; 26]. It is worthwhile that VC calculations often rely on the dimidiate pixel model, which assumes a pixel comprises vegetation and non-vegetation components, with its spectral characteristics being influenced by soil and vegetation types [27]. Consequently, the normalized difference vegetation index (NDVI) is proposed as an alternative to VC for assessment purposes. Numerous studies have investigated alterations in ecological parameters and their reactions to climate change in the broader context of global change [28; 29; 30]. However, it is important to highlight that a majority of these studies has typically examined the entire study area as a whole [24; 31; 32; 33; 34], with a limited focus on variations in ecological parameters across different land use or vegetation types in the region in response to climate change [35; 36]. For instance, studies have demonstrated significant fluctuations in the correlations between the normalized difference vegetation index (NDVI) and temperature among diverse vegetation types in Inner Mongolia [37], as well as varying associations between leaf area index (LAI) and a range of climatic factors across different vegetation types in China [24].