Abstract
Global warming has caused the change of the geographical distribution of many species and threatened the living of species on earth. It is important to describe and predict the response of these species to current and future climate changes to conserve and utilize the endemic forest species. Acer pubinerve of the Sapindaceae is an important forest tree species endemic to China, our recent fieldwork recorded A. pubinerve in the Jiangsu province for the first time, representing the northernmost known occurrence of the species. In this study, we compiled an occurrence dataset of A. pubinerve based on field investigation, herbarium specimen data and literature, and mapped the resource distribution of this endemic forest species in China. Then, we used the optimized MaxEnt model to predict the potential suitable areas of the species under current climate conditions and future climate change scenarios and studied the impacts of environmental variables on the suitable areas of the species. The MaxEnt model, optimized with a regularization multiplier of 0.5 and a feature combination of linear and quadratic terms, exhibited the best predictive performance. The prediction accuracy of the model was extremely high and the AUC values of training and test data were 0.995 and 0.998, respectively. We found that the leading environmental variables affecting the potential distribution of A. pubinerve include the mean temperature of warmest quarter, the mean temperature of driest quarter, and the annual precipitation. Under the current climatic condition, the suitable distribution area of A. pubinerve is 165.68 × 10(4) km(2), mainly located in the provinces of Zhejiang, Fujian, Jiangxi, Hunan, Guangdong, and Guangxi. Compared with the suitable area under the current climate, the total suitable areas of A. pubinerve is projected to expand toward the north under the future climate change scenarios SSP126, SSP370, and SSP585, while its center shows a general trend of westward migration. Our study lays the foundation for conservation and resource utilization of this endemic tree species in China.