From simple niche models to machine learning methods, there have been intensive efforts to understand the potentialdistribution of species in last two decades. Especially in the agricultural sector, recent SDM, Species Distribution Models,studies highly enthused to predict the potential distribution of invasive species under Climate Change. Beyond the distribution,efforts are needed to assess potential risk caused by the target pest. The Shared Socio-Economic Pathways (SSPs) are scenariosfor climate change impacts and adaptation measures. We used MaxEnt model to predict potential distribution of melonthrips with two RCPs (4.5, 8.5) and three SSPs (SSP1, SSP2, SSP3) scenarios. In agricultural land, the potential distributionof melon thrips increases under climate change, but the impact is reduced with the development-oriented scenario, SSP3.

• Jinsol Hong(Division of Environmental Science & Ecological Engineering, Korea University)
• Gwan-Seok Lee(Crop Protection Division, National Institute of Agricultural Sciences)
• Jung-Joon Park(Department of Plant Medicine, Gyungsang National University)
• Kijong Cho(Division of Environmental Science & Ecological Engineering, Korea University)