Abstract: Based on the planting data of Arabica coffee in Yunnan Province, historical meteorological data and the prediction data of different climate scenarios of CMIP6, combined with MaxEnt model, this study analyzes the key meteorological and environmental variables affecting the distribution of areas suitable for planting coffee. The distribution of climate suitable for Arabica coffee grown in Yunnan Province was extracted, and the spatio-temporal changes of suitable areas in the next 80 years （2021-2100） were deduced and analyzed. The results were as follows. Firstly, the MaxEnt model after training optimization has good performance in capturing the change characteristics of the suitable growing area of Coffea arabica in Yunnan, and the prediction efficiency of the model is AUC=0.939. Under the current climate conditions （1970-2000）, the suitable areas are basically consistent with the actual planting areas. The suitable areas are mainly distributed in western, southwestern and southern Yunnan, with a total area of about 9.66×10⁴ km². Secondly, the study obtained a set of key meteorological and environmental variables affecting the suitable distribution of Coffea arabica in Yunnan, including nine factors： annual precipitation （Bio_12）, hottest-month maximum temperature （Bio_5）, annual temperature difference （Bio_7）, September rainfall （Pre09）, December minimum temperature （Tmin12）, and altitude （Elev）. Thirdly, under different climate scenarios of CMIP6 in the future, by the end of this century, the suitable areas for Coffea arabica in Yunnan Province showed an overall reduction trend in the short term （2021-2040）, the medium term （2041-2060） and the long term （2081-2100）, of which the decline was most obvious in SSPs3-7.0. However, the total suitable areas for SSPs2-4.5 and SSPs5-8.5 would increase in the short term and decrease in the medium and long term. Spatially, the high fitness area shrinks to the core areas of Pu’er, Lincang and Xishuangbanna in Southwest Yunnan, while the non-fitness area expands slightly and the low fitness area fluctuates significantly. The results can provide reference for the layout planning of coffee industry in Yunnan Province and the formulation of long-term climate adaptation strategies.

Key words: Yunnan Arabica coffee, Maximum Entropy Model, suitable area, climate change, spatio-temporal variation