[Comparison of the potential geographical distribution of foxtail millet (Setaria italica) predicted by different models.].

Foxtail millet is one of the main food crops in arid and semi-arid areas of China. Due to its strong anti-adversity, wide adaptability and resistance against drought and barren, the foxtail millet is treated as an important strategic crop reserve for the future drought situation. In this study, data from 157 geographical distributions were used to choose 10 climatic indices, 7 soil indices and 3 topographical indices, which were based on the relationship between the foxtail millet production and the environmental factors. Four species distribution models, including maximum entropy model (MaxEnt), ecological niche factor analysis (ENFA), random forest (RF) and generalized additive model (GAM), were applied to analyze the potential geographic distribution of foxtail millet in China. The results showed that all four models did a good job in simulating the potential geographic distribution for foxtail millet and the MaxEnt model was the best one. Precipitation and temperature were most sensitive to the distribution of foxtail millet among all selected environmental factors. The outputs of models, together with the ArcGIS spatial analyst module, displayed that the total potential suitable growing regions for the foxtail millet, including the highly and moderately suitable gro-wing regions, occupied 55.68×10 km, which were much larger than the actual foxtail millet gro-wing area. The potential suitable growing regions were mainly located in northeast China, including the Northeast Plain, south of Changbai Mountain and Mudanjiang River basin, north China, including north of the Huaihe River, central China, including east of Hanjiang River and north of Dabie Mountains, northwest China, including Loess Plateau, the southern Ordos Plateau, the eastern Qilian Mountains, the eastern Tianshan Mountains and the Altai Mountains, and southwest China, including north of Chongqing and the western Guizhou Province.