## 5 Conclusions  
This study provides an example of how to use POT to rank the potential drivers of GCO and visualizes the results using HDT. The combination of POT and HDT can address the limitations encountered in previous studies, which often overlook the dynamic, integrative, synergistic, hierarchical, and spatially heterogeneous characteristics of driving factors. POT effectively handles complex interactions and nonlinear relationships among the multiple driving factors of grassland conversion, providing a comprehensive and objective analysis. By avoiding biases from linear assumptions and subjective weighting, POT ensures more accurate results and captures the hierarchical and dynamic structure of these factors through Hasse diagrams. Additionally, POT accounts for spatial heterogeneity, making it ideal for developing region-specific land-use policies tailored to diverse ecological and socioeconomic contexts. This approach not only provides a novel perspective for identifying the drivers of grassland change but also offers region-specific recommendations for grassland management. The main conclusions are as follows:1. Between 2000 and 2020, land use in the HBO region underwent significant changes. From 2000 to 2010, 6.9% of the study area experienced land-use changes, which were primarily concentrated around Hohhot and Baotou. In the period from 2010 to 2020, the proportion of land-use change increased to 11%, with a notable rise in the intensity of land-use change in the region. 2. The spatiotemporal dynamics of GCO showed significant regional differences. From 2000 to 2010, approximately 2.1% of the study area underwent GCO, mainly from grassland to cropland, bare areas, or impervious surfaces. During this period, 3.5% of the land experienced GCI, primarily from bare areas, cropland, or forest. From 2010 to 2020, the proportion of GCO increased, reflecting the intensifying impact of land-use change on the grassland ecosystem. 3. From 2000 to 2020, the primary driving factors for GCO in the HBO region were urbanization, climate change, economic development, and human activities. Urbanization was the most significant driver of large-scale GCO. Climate change, particularly drought, also played a significant role, along with economic development and human activities. This research suggests that in the future, the eastern region of the study area should prioritize addressing urban development impacts, while the western region should focus more on implementing ecological construction projects. Adopting locally tailored ecological protection and economic development strategies within the study area is crucial for achieving a win-win outcome in regional ecological conservation and economic development. Future research on POT should focus on further refining its application to complex, nonlinear systems, particularly in dynamic environmental and socioeconomic contexts. There is a need to enhance the integration of POT with other advanced analytical methods, such as AI and machine learning, to improve the prediction and visualization of land-use change processes. Additionally, expanding its application to a broader range of ecological and socioeconomic drivers across other global regions will allow for a more comprehensive understanding of regional variations and interactions. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15115906/s1](https://www.mdpi.com/article/10.3390/app15115906/s1)]([https://www.mdpi.com/article/10.3390/app15115906/s1](https://www.mdpi.com/article/10.3390/app15115906/s1)), Figure S1. All driver changes between 2000 and 2020. Figure S2. Conversion between cropland and bare areas (2000-2010, 2010-2020). (a) the map of conversion between grassland and bare area from 2000 to 2010; (b) the map of conversion between grassland and bare area from 2010 to 2020; (c) the map of conversion between grassland and cropland from 2000 to 2010; (d) the map of conversion between grassland and cropland from 2010 to 2020. Figure S3.