Protected areas are essential for the conservation of biodiversity, natural and cultural resources, and contribute to regional and global sustainable development. However, since authorities and stakeholders concern more on the conservation targets of protected areas, how to better evaluate the protected areas' contributions to sustainable development goals (SDGs) remains generally understudied. To fill this knowledge gap, we chose the Qinghai-Tibet Plateau (QTP) as the study area, mapped the SDGs in 2010, 2015 and 2020, detecting the interactive relationships among SDGs. Then we used the landscape pattern indices and ecosystem service (ES) proxies to describe the characteristics of national nature reserves (NNRs), and explore the contributions of protected areas to SDGs using panel data models. The results showed that from 2010 to 2020, most cities of QTP improved their SDG scores to >60. The three cities with the best SDG performance improved their average scores by nearly 20 %. Among the 69 pairs correlations of SDG indicators, 13 synergies and 6 trade-offs were observed. About 65 % of the SDG indicators were significantly correlated with landscape pattern or ESs of NNRs. Carbon sequestration had a significant positive effect on 30 % of the SDG indicators, while habitat quality had a negative effect on 18 % of the SDG indicators. For the landscape pattern indices, the largest patch index had a significant positive effect on 18 % of the SDG indicators. This study highlighted that the ESs and landscape pattern could well quantify the contribution of protected areas to SDGs, which can provide essential implications for protected area management and regional sustainable development.