Abstract
Panax notoginseng is a well-known research species in China. The issue of continuous crop barriers has led to a reduction in suitable habitats in Wenshan. In the context of global warming, it is far from adequate to merely predict the suitability distribution of P. notoginseng under future climate, as it remains unclear whether the Highly suitable habitats in the results are also the high content areas. We used machine learning for the first time to predict the changes in chemical components under future climate scenarios and found that it was more scientific than the Biomod2 based on environmental variables. The results show that TreeBagger is an effective tool to predict the chemical composition of P. notoginseng under future climate change. Bio7 was an important environmental variable affecting the distribution of P. notoginseng, and Bio15 was the environmental variable that had the greatest impact on the quality of P. notoginseng. Comprehensive evaluation indicated that Pre11 might be a key factor affecting the distribution and quality of P. notoginseng. In the future, under climate change, most of the Highly suitable habitats for P. notoginseng in Wenshan area will be downgraded to moderately suitable and lowly suitable areas. Therefore, it is necessary to focus on protecting its ecosystem and plan the cultivation of P. notoginseng in Yuxi and its surrounding areas, which can effectively relieve the cultivation pressure in Wenshan area. This study can provide new ideas and methods for the future research on the species distribution of medicinal plants.