The climate oscillations of the quaternary periods have profoundly affected the geographic distributions of current species. Acer davidii is a deciduous forest tree species mainly distributed in East Asia and China, playing a dominant role in the local forest ecosystem. In order to study the potential changes of geographic distributions of A. davidii in climate fluctuations, we collected the relate geographical distribution data and six climatic variables, using maximum entropy modelling to determine the species distribution. The results showed that the Areas Under Curve (AUC) values of the working characteristic curves of the subjects in the five historical periods were all greater than 0.93, suggesting that the results of maximum entropy modelling were accurate. The simulation of species distribution showed that the suitable area of A. davidii was mainly concentrated in central and northern China in contemporary times. From the Last Interglacial Age (LIG) to the Last Glacial Maximum (LGM), and then to the future (2050, 2070), the distribution area of this species experienced a decrease (LGM~Current; the high adaptability areas of central China became moderate) then an increase (Current~2050, the adaptation areas expanded to South Asia, Southeast Asia, and Siberia), and finally decreased (2050~2070, the suitable areas of South Asia, Southeast Asia, and Siberia shrank returning to China at latitude 25 °N). Compared to the LGM, the area of contemporary suitable area increased. Interestingly, the area of suitable growth range under future climatic conditions (2050) increased by half than before, and the suitable distribution area moved from Midwest China to Northeast China. This study on the change of species distribution can provide a typical case for the model study on the response of plants to climate change in the north temperate and subtropical zones of East Asia. Meanwhile, it can also give a basis for planting planning, species protection, and management.
Distribution of
Bactrocera oleae
(Rossi, 1790) throughout the Iberian Peninsula based on a maximum entropy modelling approach
