Assessing the impact of climate change on habitat dynamics of Hovenia dulcis in China using the MaxEnt model

Xi Li^1,2Peiyao Li^1,2Qi-Qing Cheng^1,2*Li Shimeng^1,2Mingli Hu^1,2Yankun Li^1,2Ming Rong Yang^3,4Yuanxin Li^1,2Shi Wang^1,2Ting Shu^1,2

• ¹Hubei University of Science and Technology, Xianning, China
• ²Hubei University of Science and Technology School of Pharmacy, Xianning, China
• ³Macau University of Science and Technology, Taipa, Macao, SAR China
• ⁴University of Macau Institute of Chinese Medical Science, Taipa, Macao, SAR China

Introduction: Hovenia dulcis Thunberg, a multifunctional medicinal plant native to East and Southeast Asia, has been introduced worldwide. However, the environmental factors that determine its habitat and its precise distribution in China remain incompletely characterized. Methods: Therefore, the Maximum Entropy (MaxEnt) model integrated with, ArcGIS was employed to predict the potential distribution of H. dulcis in China, using 479 initial occurrence records (which were spatially filtered to 191 points) and 33 environmental variables (of which 15 were selected for the final analysis). Model performance was assessed via AUC-ROC, with key variables identified through permutation importance and response curves. Future projections were made under SSP126 and SSP585 scenarios for the 2050s and 2090s. Results: The model demonstrated high accuracy (AUC = 0.934). The distribution of H. dulcis was primarily governed by annual precipitation (Bio12), the minimum temperature of the coldest month (Bio06), elevation, and the mean diurnal temperature range (Bio02). The optimal ranges for these variables were as follows: annual precipitation of 708.5–2,956.8 mm, a minimum temperature of the coldest month between -4.9 and 8.9 °C, elevation of 273.9–1,019.4 m, and a mean diurnal temperature range of 6.81–10.18 °C. At present, suitable habitats are concentrated in central and southwestern China. Future projections indicate a northward shift and altitudinal increase in suitable areas, with expansions in Beijing, Hebei, and Liaoning, but contractions in Guangxi and Shandong. Hunan, Jiangxi, Sichuan, and Guizhou remain core suitable regions. This northward shift is consistent with preference of H. dulcis for the warm temperatures and adequate humidity, highlighting both its vulnerability and its adaptive potential under global warming. Discussion: H. dulcis is highly sensitive to climatic variables, particularly temperature and precipitation. Our findings provide a scientific basis for developing well-targeted conservation strategies, promoting sustainable utilization, and optimizing cultivation practices for H. dulcis under climate change.