National parks, as an important type of nature protected areas, are the cornerstone that can effectively maintain biodiversity and mitigate global climate change. At present, China is making every effort to build a nature-protection system, with national parks as the main body, and this approach considers China′s urgent goals of obtaining carbon neutrality and mitigating climate change. It is of great significance to the national carbon-neutralization strategy to accurately predict the carbon sink capacity of national park ecosystems under the background of global change. To evaluate and predict the dynamics of the carbon sink capacity of national parks under climate change and different management measures, we combined remote-sensing observations, model simulations and scenario analyses to simulate the change in the carbon sink capacity of the proposed Kunlun Mountain National Park ecosystem over the past two decades (2000–2020) and the change in the carbon sink capacity under different zoning controls and various climate change scenarios from 2020 to 2060. Our results show that the carbon sink capacity of the proposed Kunlun Mountain National Park area is increasing. Simultaneously, the carbon sink capacity will be improved with the implementation of park management and control measures; which will be increased by 2.04% to 2.13% by 2060 in the research area under multiple climate change scenarios. The research results provide a scientific basis for the establishment and final boundary determination of the proposed Kunlun Mountain National Park.

The protected area network (PAN) is a vital strategy for enhancing ecological integrity and connectivity. However, its contributions to the Kunming–Montreal Global Biodiversity Framework (GBF) 2030 Targets and Sustainable Development Goals (SDGs) remain understudied due to limited indicator assessments and regional case comparisons. This study applied circuit theory to construct and optimize a PAN in China's coastal region. First, resistance surfaces were mapped, connectivity corridors identified, and network key points determined. Second, the network structure was analyzed to classify source areas and corridors by importance and to identify potential conservation zones. Finally, the PAN's contributions to GBF Targets 2 and 3, SDG 15 indicators, and related synergistic benefits were quantified using coverage‐based performance metrics and spatial analysis. The results show that the PAN raises protected‐area coverage to 33.3%, meeting the GBF 30 × 30 target, boosts SDG 15 terrestrial protection by 50% above the regional average, and supports other SDGs. Key connectivity points align along the coastal belt, with eight regions exhibiting both pinch points and barriers, underscoring the complexity of coastal–terrestrial ecotones. This study highlights the unique role of coastal PANs in global conservation and recommends refined assessment frameworks and collaborative planning to enhance their international applicability.