Ecological protection and restoration results in a series of complicated changes in land cover. Lack of research on the historical and potential effects of land cover change on ecosystem service value (ESV) hinders decision-making on trade-offs involved in environmental management. To address this gap, the effects of land cover change on ESV in the upper reaches of the Heihe River Basin in northwestern China were evaluated. First, on the basis of land cover maps for 2001, 2008 and 2015, the land cover map for 2029 was predicted with CA-Markov model. Then, the changes in ESV resulting from land cover change were valuated with the benefit transfer method. The results showed that the total ESV increased from $1207.33 million (USD) in 2001 to $1479.48 million (USD) in 2015, and the value was expected to reach $1574.53 million (USD) in 2029. The increase in ESV can be mainly attributed to expansion in areas of wetland. In this study, the elastic index was applied to identify areas that were more sensitive to ecological management, aiding in selecting sites for investment in ecological protection and restoration programs. Furthermore, the potential effects of land cover change on ESV was evaluated. The results are of great importance for guiding future ecological management.The Heihe River is the second largest inland river in China, originating in the Qilian Mountains and flowing into the Inner Mongolia Plateau. Serving as the water source that supports sustainability of the agricultural ecosystems in the middle reaches and the stability of the ecosystems in the lower reaches, the upper reaches of the Heihe River Basin are an ideal case for ecological protection and restoration in northwestern China [17]. Since 2001, the scale of and investment in protecting and restoring natural asset have been greatly expanded. Accurate evaluation of effects of land cover change on ESV can support the decision-making process regarding the trade-offs involved in ecological management [18].Land cover change is a complex process with both spatial and temporal dimensions [19][20][21][22]. Currently, many models are developed to simulate future land cover change [23,24]. Most of the models, such as LUSD (Land Use Scenario Dynamics) [25], CLUE-S (Conversion of Land Use and its Effects at Small regional extent) [26], are more suitable for application in urban regions, rather than areas that are mostly covered by vegetation. While the CA-Markov (Cellular Automata-Markov) model can be applied in different areas. The hybrid model can simulate the spatial variation of complex systems with the Cellular Automata (CA) [27], and long-term predictions with the Markov Chain [28]. More importantly, the CA-Markov model allows setting goals of ecological protection and restoration programs as constrains, and setting habitats of various vegetation types as factors when producing suitability maps, thereby increasing the simulation accuracy in regions that are mostly covered by vegetation.To date, theoretical and methodological frameworks have been establ...