## 5 Conclusions  
This study elucidated the spatial and temporal dynamics of forest and grassland ecosystems within the Altai Mountains National Park Candidate Area, revealing significant forest expansion by 13.65% and grassland degradation by 11.69% over the last two decades. By leveraging analytical methods, we identified key drivers of these ecosystem changes, including soil type, elevation, and cropland expansion, with cropland accounting for 20.29% of the impact on grassland dynamics. These findings provide a detailed understanding of the complex interactions shaping these landscapes, including the differential influences of biophysical and anthropogenic factors. Furthermore, this study proposed a framework for conservation and management that focuses on identifying critical drivers of ecosystem change, informing targeted conservation strategies, and evaluating the effectiveness of existing protected areas. Our analysis showed that forest restoration within protected areas was 1168.68 m\({}^{2}\) higher on average than in unprotected areas, while grassland loss was 3007.42 m\({}^{2}\) higher, highlighting the challenges faced in grassland conservation. Using the Altai Mountains National Park Candidate Area as a case study, we demonstrated the variability in conservation outcomes and emphasized the need for balanced management approaches that effectively target both forest and grassland conservation. The insights derived from this research hold substantial potential to inform the formal establishment of the Altai Mountains National Park and enhance conservation planning. Moreover, the proposed framework can be broadly applied to delineate potential protected areas at regional scales worldwide, ultimately contributing to more effective and adaptive ecosystem management. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/land14010048/s1](https://www.mdpi.com/article/10.3390/land14010048/s1)]([https://www.mdpi.com/article/10.3390/land14010048/s1](https://www.mdpi.com/article/10.3390/land14010048/s1)), Figure S1: The location of the field verification in the Altai National Park Candidate Area; Figure S2: The location of the forest gravity center and the standard deviation ellipse in the Altai National Park Candidate Area from 2000 to 2020; Figure S3: The location of the grassland gravity center and the standard deviation ellipse in the Altai National Park Candidate Area from 2000 to 2020; Figure S4: The spatial distributions of all factors (\(\times\)1: elevation, \(\times\)2: slope, \(\times\)3: average annual temperature trends, \(\times\)4: average annual precipitation trends, \(\times\)5: SPEI trends, \(\times\)6: GPP trends, \(\times\)7: soil type, \(\times\)8: grazing intensity trends, \(\times\)9: cropland trends, \(\times\)10: population distribution trends, \(\times\)11: distribution of tourist attractions, \(\times\)12: distribution of mining sites); Figure S5: The distribution of protected areas in the Altai National Park Candidate Area (Kanas: Xinjiang Kanas National Nature Reserve. Baihaba: Baihaba National Forest Park. Keketuohai: Irtysh Keketuohai Wetland Nature Reserve. Habahe: Xinjiang Habahe Birch National Forest Park. Jiadengyu: Jiadengyu National Forest Park. Kanas GeoPark: Xinjiang Burqin Kanas Lake National GeoPark. Akeqi: Xinjiang Habahe Akeqi National Wetland Park. Burqin: Xinjiang Burqin National GeoPark); Table S1: Data source of driving factors; Table S2: Results of PSM for average treatment effect on the treated (ATT) in protected areas during 2000-2020. Conceptualization, M.D. and F.H. ; methodology, M.D. ; software, M.D. ; validation, M.D. and F.H. ; formal analysis, M.D. ; investigation, M.D., F.H. and W.M. ; data curation, M.D. ; writing--original draft preparation, M.D. ; writing--review and editing, M.D., F.H., W.Y. and W.M. ; visualization, M.D. ; supervision, X.L. ; project administration, X.L. ; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript.