Prediction of potential distribution of seven plant species of <em>Aster</em> (Asteraceae) based on MaxEnt model

Aster (Asteraceae) species, as one of the traditional Tibetan medicinal plants in China, have high useful medicinal and unique ornamental value, the market demand has been gradually increasing. In this study, seven species of Aster were selected from Qinghai-Tibet Plateau, and the MaxEnt model was used to investigate their potential distribution in China and the changes in their suitable habitat under future climate conditions based on the current survey and distribution data of specimens on the site and six to eight environmental variables. The results showed that temperature and precipitation were important limiting factors affecting the distribution of Aster, and Bio2, Bio3, and Bio10 were common environmental factors influencing factors of Aster species. Under the current climate, the mainly potential distributed region of the seven Aster species in the Qinghai-Tibet Plateau. Under projected future climate scenarios, the suitable habitats of A. asteroides and A. diplostephioides will shrink significantly, while those of A. farreri, A. poliothamnus, A. souliei, A. tongolensis, and A. yunnanensis var. labrangensis will expand accordingly. Environmental factors provide a large gain in predicting the distribution of Aster species. Among the environmental variables, isothermality (Bio3) induced the largest impact on SDM and contained the most useful information for A. diplostephioides (55.9%), A. souliei (41.5%) and A. yunnanensis var .labrangensis (27.1%), while A. tongolensis (27.9%) and A. poliothamnus (26.8%) were more significantly affected by the temperature seasonality (Bio4), A. asteroides (66.3%) and A. farreri (21%) was more significantly affected by the mean temperature of warmest quarter (Bio10). The study findings suggest that the distribution range of seven species of Aster will be greatly impacted by climate change. This research helps identify the limiting factors affecting the natural distribution and potential suitable areas for Aster species, which can inform conservation efforts, plant introduction, acclimatization, domestication, and cultivation of Aster. Methods The dataset includes 13 environmental factors: Mean Diurnal Range (Bio 2); Isothermality (Bio 2/ Bio 7) (×100) (Bio 3); Temperature Seasonality (standard deviation ×100) (Bio 4); Min Temperature of Coldest Month (Bio 6); Mean Temperature of Wettest Quarter (Bio 8); Mean Temperature of Driest Quarter (Bio 9); Mean Temperature of Warmest Quarter (Bio 10); Mean Temperature of Coldest Quarter (Bio 11); Annual Precipitation (Bio 12); Precipitation of Driest Month (Bio 14); Precipitation Seasonality (Coefficient of Variation) (Bio 15); Precipitation of Warmest Quarter (Bio 18); Precipitation of Coldest Quarter (Bio 19). The data format is an ASC file. Data for bioclimatic variables include present (1970-2000), future: 2041-2060, 2081-2100. Each future period includes four shared socioeconomic pathways (ssp_126, ssp_245, ssp _370, ssp_585). Sharing/accessing information The data sources are listed below: Chinese Herbarium Resource Centre (https://www.cvh.org.cn) Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/) Published papers. Author's field fieldwork. WorldClim database (https://www.worldclim.org/) Geospatial data cloud (https://www.gscloud.cn/home) Hardware The dataset was filtered and validated using ArcGIS 10.4 (GIS) software. Pre-modelling was performed using the MaxEnt model.