Reduced vegetation growth ultimately induces degradation of the ecosystem and CO 2 sequestration. Multiple risks can affect vegetation, but climate change and human influence have been particularly known to be major risks for deteriorating the ecosystem. However, there is limited information illustrating comprehensive impact pathways that consider both climatic and human impacts on vegetation. To promote optimum decision-making, information is required to elucidate complex cause-and-effect pathways in order to determine how various impacts are related and which ones are more important. Hence, we identified impact pathways affecting enhanced vegetation index (EVI) regarding climate and human factors by revealing a causal network using the Bayesian network approach. Vulnerable vegetation types and the spatial range of impact were evaluated based on the identified network by analyzing temporal changes in annual average EVI, human-induced land conversion, and multiple climate extremes from 2002 to 2014 on Jeju Island, South Korea. The results indicated the high vulnerability of coniferous forests compared with mixed and deciduous forests were able to elucidate the major impact paths, including human-induced land conversion at lower elevation, length of frost, degree of heat, and general intensity of wetness (Pearson's r = 0.58). Existing policies in the study site have been insufficient to avoid the major paths influencing vegetation state. This study offers insights into comprehensive impact paths in order to support effective decision-making for nature conservation.