The aim of this article is to analyze the impact of land use changes on trade-offs/synergies of the ecosystem service in Gangu County, Gansu province, China, from 2000 to 2020, and intends to provide a reference for decision-making on regional ecological environment protection and restoration. We analyzed the land use changes in Gangu County with the dynamic degree of single land use. Changes in ecosystem service values (ESV) were analyzed using the equivalent factor method. The temporal and spatial distribution patterns of ecosystem service trade-offs/synergies were elaborated with the help of the correlation coefficient method and local autocorrelation analysis. The impact of land use change on trade-offs/synergies of ecosystem service was analyzed according to the ecological contribution rate of land use changing and the changing of land use area. The results showed that: (1) cultivated land and grassland were the dominant land use types in Gangu County, China; the largest increase in the dynamic degree of single land use was in construction land, followed by grassland, and the largest decrease in the dynamic degree of single land use was in unused land, followed by grassland. (2) Between 2000 and 2020, the ESV showed an upward trend; the regulating service provided the largest part of the ESV among the four first ecosystem service types. The medium ESV zone occupied the largest area, and the spatial distribution pattern of ESV was high in the south and low in the north of Gangu County, China. (3) The relationships of ecosystem services were dominated by synergistic and supplemented by trade-offs. The strongest synergistic relationship was expressed between EP and BP, then, between EP and AL. Meanwhile, the strongest trade-off relationship was carried out between BP and FP. During the 20 years, the relationship of ecosystem service showed a weak shift from mainly synergistic to trade-off temporally. Spatially, the synergistic relationship was dominated and concentrated in the central and southern parts of the study area. (4) The increase in the area of grassland and forest land were the root causes resulting in the increase of ESV in Gangu County. In the time dimension, land use change had the greatest impact on the trade-off synergistic relationship between FP and all other services. In the spatial dimension, land use change has little impact on trade-offs/synergies in the northern region and more in the central and southern regions of Gangu County. The results of this study can provide a scientific basis for improving the ecological environment and promoting sustainable development in Gangu County. At the same time, it will lay the foundation for the region to realize a win–win situation between economic development and ecological protection.

This study selected the five indicators of soil erosion, climate environment, geological hazards, biodiversity, and human disturbances and uses the entropy weight method to calculate the ecological sensitivity of the West Qinling Mountains from 2000 to 2020. The analysis produced a spatiotemporal distribution of ecological sensitivity over the 20-year period. An equal step size of 500 m was used to progressively increase the spatial scale from 500 m to 6 km. The optimal scale for the spatial differentiation of ecological sensitivity in the West Qinling Mountains was determined by analyzing the characteristics of changes at different scales, response mechanisms, and optimal parameters for geographical detector spatial scale identification. Based on this scale, the change in intensity and pattern and the influencing factors of ecological sensitivity were analyzed. The results show the following: (1) The 5.5 km spatial scale balances the requirements of accuracy, spatial heterogeneity, and data adequacy, making it the optimal scale for analyzing the spatiotemporal variation patterns of ecological sensitivity in the West Qinling Mountains. (2) From 2000 to 2020, the mean ecological sensitivity in the West Qinling Mountains exhibited a decreasing trend, indicating an improvement in the ecological environment. Spatially, the ecological sensitivity of the West Qinling Mountains showed a spatial distribution pattern of “low in the west and high in the east, low in the south and high in the north”. During the study period, the ecological sensitivity in the West Qinling region remained generally stable, with no high-frequency changes observed. (3) Population density is the primary driving factor of spatial differentiation of ecological sensitivity in the West Qinling Mountains, while GDP serves as a secondary factor. Overall, socioeconomic factors have the most significant impact on ecological sensitivity. (4) Over 75% of the ecological sensitivity trends exhibit patterns of perennial unchanged and fluctuating unchanged trends, with areas of fluctuating increase smaller than areas of fluctuating decrease. Regions of perennial high sensitivity are primarily concentrated in the northeastern part of the West Qinling Mountains, while areas with increased fluctuation in ecological sensitivity are mainly located in the western and southern parts of the West Qinling Mountains. Future efforts should focus on these regions.