The Qinghai-Xizang Plateau is the largest ecologically fragile and sensitive area in China and clarifying the spatial and temporal characteristics of ecological vulnerability of the Qinghai-Xizang Plateau Nature Reserve is important to promote the synergistic enhancement of the ecological security barrier and green development. Taking the Qinghai-Xizang Plateau Nature Reserve as a case study, we constructed a system of evaluation indicators and quantitatively evaluated the spatial and temporal characteristics based on the three dimensions of sensitivity-importance-resilience （SIR）. We also simulated the scenarios of ecological vulnerability under different decision-making preferences by using AHP-OWA. The results showed that： ① From 2000 to 2020, the ecological vulnerability index （EVI） of the Qinghai-Xizang Plateau decreased from 0.79 to 0.74, and the ecological vulnerability pattern of the nature reserves showed a trend of improvement； however, the higher vulnerability areas were still dominant. ② The spatial pattern of ecological vulnerability showed a general pattern of "high in the northwest and low in the southeast," with the high values mainly concentrated in the northwest and low values in the southeast. The high values were mainly concentrated in Qiangtang, Cocozily, Zhongkunlun, and Arjinshan, and the low values were located in the southeast of Yarlung Zangbo River and Ruoergai Wetland Nature Reserve. ③ Based on the OWA method, three scenarios were set up, from the sustainability-oriented to the economy-priority oriented, and the scope of the highly fragile area was expanding, with the Qiangtang and Arjinshan regions being more obvious, and the changes in the low fragile area being lesser. This study assessed the ecological vulnerability of the Qinghai-Xizang Plateau Nature Reserve and simulated the future scenarios of vulnerability under different development conditions through the OWA method, which can provide theoretical references for the construction of regional sustainable development and vulnerability risk early warning mechanisms.